Job Matches
Washington job postings for occupations your coursework prepares you for. Sorted by how many of the occupation's tasks your courses cover.
Showing CareerOneStop postings from the last 30 days; the scraper re-syncs from CareerOneStop nightly. Last posting in this list dated 2026-06-06.
Scraper last re-confirmed a WA posting 2026-06-06 02:56 (113 touched today).
- Mentor others on mathematical techniques.
- Maintain knowledge in the field by reading professional journals, talking with other mathematicians, and attending professional conferences.
- Develop new principles and new relationships between existing mathematical principles to advance mathematical science.
-
Disseminate research by writing reports, publishing papers, or presenting at professional conferences.
via MATH 491
- Assemble sets of assumptions, and explore the consequences of each set.
Biostatistician, HEOR Consulting Services Company: Norstella Location: Remote, United States Date Posted: May 20, 2026 Employment Type: Full Time Job ID: R-1976 Description About Norstella Norstella is a premier and critical global life sciences data and AI solutions platfor
- Advanced degree (MS or PhD) in Biostatistics, Statistics, or a related quantitative field.
- At least 3 years of professional experience as a biostatistician/statistician using real-world data or clinical trial data in the pharmaceutical, biopharmaceutical, medical device, or CRO/consulting environment.
- Strong proficiency in statistical programming using R (technical proficiency will be tested). Additional proficiency in SQL or Python is valued.
- Ability and willingness to train and work within the Panalgo IHD analytics platform.
- Norstella's HEOR Services team is seeking an experienced biostatistician to develop statistical analysis plans and perform advanced statistical analysis on non-interventional observational research st… Norstella's HEOR Services team is seeking an experienced biostatistician to develop statistical analysis plans and perform advanced statistical analysis on non-interventional observational research studies using real world data. This role will advise internal and external clients on recommended statistical approaches to support study research objectives, and will be directly responsible for documentation, implementation, and interpretation of statistical analysis plans. The ideal candidate brings deep expertise with realworld data, strong R programming skills, and a track record of applying advanced statistical methods to support regulatory, epidemiology, HEOR, and RWE use cases.
- Support senior HEOR leaders with non-interventional observational research study design, advanced statistical analysis, and interpretation using NorstellaLinQ Realworld Data to support regulatory, epi… Support senior HEOR leaders with non-interventional observational research study design, advanced statistical analysis, and interpretation using NorstellaLinQ Realworld Data to support regulatory, epidemiology, HEOR, and RWE use cases.
- During study design phase, recommend appropriate statistical methods to address study research objectives (e.g., power calculations, methods to mitigate selection bias, development of matched cohorts,… During study design phase, recommend appropriate statistical methods to address study research objectives (e.g., power calculations, methods to mitigate selection bias, development of matched cohorts, development of measures from multiple sources [e.g., EMR + claims], analysis of NLP-derived measures from unstructured EMR, approach for outcomes that require time-to-event analysis with competing risk, multivariable modeling, repeated measures, time-averaged clinical measures, causal inference, and techniques for analyzing rare and ultra rare populations including Bayesian statistics).
- Write statistical analysis plans to address the above considerations.
- Analyze and interpret statistical data to identify significant differences in relationships among sources of information.
- Evaluate the statistical methods and procedures used to obtain data to ensure validity, applicability, efficiency, and accuracy.
- Report results of statistical analyses, including information in the form of graphs, charts, and tables.
- Determine whether statistical methods are appropriate, based on user needs or research questions of interest.
- Prepare data for processing by organizing information, checking for inaccuracies, and adjusting and weighting the raw data.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze and interpret statistical data to identify significant differences in relationships among sources of information.
- Evaluate the statistical methods and procedures used to obtain data to ensure validity, applicability, efficiency, and accuracy.
- Report results of statistical analyses, including information in the form of graphs, charts, and tables.
- Determine whether statistical methods are appropriate, based on user needs or research questions of interest.
- Prepare data for processing by organizing information, checking for inaccuracies, and adjusting and weighting the raw data.
These could be filled by an applied project, elective, or internship — see the program page for examples.
We made history and now we work to transform the future - for our customers, our communities and our families. You'll see your work on the road every day, helping people move freely and pursue their dreams. At Ford, you can build more than vehicles. Come build what matters. Do you believe data tel
- Accelerate the application of value-added analytics and machine learning into the portfolio of products for Manufacturing Analytics.
- Drive analytic excellence into product teams by collaborating with Data Scientists, Data Engineers and Software Engineers in analytic and machine learning methods.
- Work closely with the Product Manager and Product Owner to translate Business Value needs into analytic deliverables and, where appropriate, software products for delivery by product teams.
- Work hands-on with the team and other partners to deliver solutions that meet our customer's requirements and needs.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Plan, coordinate, and implement security measures to safeguard information in computer files against accidental or unauthorized damage, modification or disclosure.
-
Test programs or databases, correct errors, and make necessary modifications.
via CSCD 210
-
Train users and answer questions.
via CSCD 484
-
Develop standards and guidelines for the use and acquisition of software and to protect vulnerable information.
via MATH 491
-
Write and code logical and physical database descriptions and specify identifiers of database to management system, or direct others in coding descriptions.
via CSCD 300
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Plan, coordinate, and implement security measures to safeguard information in computer files against accidental or unauthorized damage, modification or disclosure.
-
Test programs or databases, correct errors, and make necessary modifications.
via CSCD 210
-
Train users and answer questions.
via CSCD 484
-
Develop standards and guidelines for the use and acquisition of software and to protect vulnerable information.
via MATH 491
-
Write and code logical and physical database descriptions and specify identifiers of database to management system, or direct others in coding descriptions.
via CSCD 300
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Plan, coordinate, and implement security measures to safeguard information in computer files against accidental or unauthorized damage, modification or disclosure.
-
Test programs or databases, correct errors, and make necessary modifications.
via CSCD 210
-
Train users and answer questions.
via CSCD 484
-
Develop standards and guidelines for the use and acquisition of software and to protect vulnerable information.
via MATH 491
-
Write and code logical and physical database descriptions and specify identifiers of database to management system, or direct others in coding descriptions.
via CSCD 300
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Plan, coordinate, and implement security measures to safeguard information in computer files against accidental or unauthorized damage, modification or disclosure.
-
Test programs or databases, correct errors, and make necessary modifications.
via CSCD 210
-
Train users and answer questions.
via CSCD 484
-
Develop standards and guidelines for the use and acquisition of software and to protect vulnerable information.
via MATH 491
-
Write and code logical and physical database descriptions and specify identifiers of database to management system, or direct others in coding descriptions.
via CSCD 300
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Plan, coordinate, and implement security measures to safeguard information in computer files against accidental or unauthorized damage, modification or disclosure.
-
Test programs or databases, correct errors, and make necessary modifications.
via CSCD 210
-
Train users and answer questions.
via CSCD 484
-
Develop standards and guidelines for the use and acquisition of software and to protect vulnerable information.
via MATH 491
-
Write and code logical and physical database descriptions and specify identifiers of database to management system, or direct others in coding descriptions.
via CSCD 300
These could be filled by an applied project, elective, or internship — see the program page for examples.
- Plan, coordinate, and implement security measures to safeguard information in computer files against accidental or unauthorized damage, modification or disclosure.
-
Test programs or databases, correct errors, and make necessary modifications.
via CSCD 210
-
Train users and answer questions.
via CSCD 484
-
Develop standards and guidelines for the use and acquisition of software and to protect vulnerable information.
via MATH 491
-
Write and code logical and physical database descriptions and specify identifiers of database to management system, or direct others in coding descriptions.
via CSCD 300
These could be filled by an applied project, elective, or internship — see the program page for examples.
-
Generate standard or custom reports summarizing business, financial, or economic data for review by executives, managers, clients, and other stakeholders.
via MATH 491
-
Provide technical support for existing reports, dashboards, or other tools.
via MATH 491
- Document specifications for business intelligence or information technology reports, dashboards, or other outputs.
-
Disseminate information regarding tools, reports, or metadata enhancements.
via MATH 491
-
Analyze competitive market strategies through analysis of related product, market, or share trends.
via MATH 491
These could be filled by an applied project, elective, or internship — see the program page for examples.
Become a part of our caring community The Business Intelligence Engineer 2 solves complex business problems and issues using data from internal and external sources to provide insight to decision-makers. The Business Intelligence Engineer 2 work assignments are varied and frequently require in
- 2+ years of experience in Python or Pyspark
- 2+ years of experience in Jupyter Notebook environment
- 2+ years of experience in Databricks Platform
- 2+ years of experience in Microsoft PowerBI or other data visualization software
- Experience in Managed Care
- Experience in Medicaid
- Experience in risk adjustment
- Experience with data mining and predictive modeling techniques
-
Generate standard or custom reports summarizing business, financial, or economic data for review by executives, managers, clients, and other stakeholders.
via MATH 491
-
Provide technical support for existing reports, dashboards, or other tools.
via MATH 491
- Document specifications for business intelligence or information technology reports, dashboards, or other outputs.
-
Disseminate information regarding tools, reports, or metadata enhancements.
via MATH 491
-
Analyze competitive market strategies through analysis of related product, market, or share trends.
via MATH 491
These could be filled by an applied project, elective, or internship — see the program page for examples.
About Us SolomonEdwardsGroup, LLC ("SolomonEdwards") is a full-service professional services firm offering financial, operational, and technology consulting and operations support. We work with some of the world's most prominent companies to help them envision and achieve a better future. We k
- · High School Diploma or equivalent required.
- · Bachelor's degree preferred.
- · Master of Library and Information Science (MLIS) strongly preferred.
- · Experience working with large datasets across multiple applications.
- We are seeking a Data Analyst to join a leading global media and entertainment organization with operations across multiple business units and extensive archival collections. This role will support en… We are seeking a Data Analyst to join a leading global media and entertainment organization with operations across multiple business units and extensive archival collections. This role will support enterprise-wide data migration, metadata management, digital asset inventory, and reporting initiatives focused on modernizing legacy systems and improving data accessibility, quality, and governance.
- · Analyze legacy datasets to support data cleanup, consolidation, and standardization initiatives.
- · Perform data mining, validation, and quality control across multiple systems.
- · Manage metadata, inventory records, and digital asset information.
-
Generate standard or custom reports summarizing business, financial, or economic data for review by executives, managers, clients, and other stakeholders.
via MATH 491
-
Provide technical support for existing reports, dashboards, or other tools.
via MATH 491
- Document specifications for business intelligence or information technology reports, dashboards, or other outputs.
-
Disseminate information regarding tools, reports, or metadata enhancements.
via MATH 491
-
Analyze competitive market strategies through analysis of related product, market, or share trends.
via MATH 491
These could be filled by an applied project, elective, or internship — see the program page for examples.
RWD Data Analyst Company: Norstella Location: Remote, United States Date Posted: Jun 1, 2026 Employment Type: Full Time Job ID: R-1998 Description Why Norstella? Norstella unites market-leading companies that all have a shared goal of improving patient access. Each organization (C
- Bachelor's degree in Data Science, Computer Science, Public Health, Biostatistics, Epidemiology, or a related field
- 2-5 years of hands-on experience with real-world healthcare data, with demonstrated ability to assess source suitability and formulate data-driven recommendations
- Comprehensive knowledge of RWD source types - including claims, EHR/EMR, laboratory, and unstructured data - and the ability to articulate appropriate use cases for each
- Prior experience investigating unstructured or semi-structured EMR data, including identification of analytically viable variables within complex source formats
- Norstella's Real-World Data (RWD) team is seeking a mid-level Data Analyst with demonstrated expertise in real-world healthcare data. This role is designed for an analytically rigorous professional wh… Norstella's Real-World Data (RWD) team is seeking a mid-level Data Analyst with demonstrated expertise in real-world healthcare data. This role is designed for an analytically rigorous professional who applies critical thinking to each data engagement - evaluating source suitability, informing methodological decisions, and delivering outputs that reflect both technical precision and clinical reasoning.
- The successful candidate will possess a thorough understanding of RWD source types and their respective limitations, and will be expected to make substantive, well-supported recommendations on data se… The successful candidate will possess a thorough understanding of RWD source types and their respective limitations, and will be expected to make substantive, well-supported recommendations on data selection, inclusion and exclusion criteria, and analytical approach. This individual will serve as a trusted technical resource for internal teams and client-facing stakeholders, translating complex requirements into sound data strategies while proactively identifying risks and driving issues to resolution.
- While the role requires strong technical proficiency, candidates are expected to bring a consultative orientation to their work - engaging with client needs, contributing to product decisions, and con… While the role requires strong technical proficiency, candidates are expected to bring a consultative orientation to their work - engaging with client needs, contributing to product decisions, and consistently seeking to improve outcomes rather than simply executing against defined specifications.
- *_RWD Expertise & Data Advisory_
- Experience working with vendor-delivered data products, including familiarity with delivery formats, data dictionaries, and source-specific quality considerations
- Exposure to RWD product development, including participation in decisions regarding data asset design or feature prioritization
- Experience translating clinical or scientific documentation into executable database logic
- Proficiency with data analysis and pipeline tools such as Python, R, Airflow, or equivalent
-
Generate standard or custom reports summarizing business, financial, or economic data for review by executives, managers, clients, and other stakeholders.
via MATH 491
-
Provide technical support for existing reports, dashboards, or other tools.
via MATH 491
- Document specifications for business intelligence or information technology reports, dashboards, or other outputs.
-
Disseminate information regarding tools, reports, or metadata enhancements.
via MATH 491
-
Analyze competitive market strategies through analysis of related product, market, or share trends.
via MATH 491
These could be filled by an applied project, elective, or internship — see the program page for examples.
Become a part of our caring community A Medicaid Business Intelligence Engineer solves complex business problems and issues using data from internal and external sources to provide insight to decision-makers. The Business Intelligence Engineer work assignments are varied and frequently require
- 2+ years of experience in Python and Pandas Python library.
- 2+ years of experience in Jupyter Notebook environment.
- 2+ years of experience in Databricks Platform.
- 2+ years of experience in Microsoft PowerBI or other data visualization software.
- Experience in Managed Care.
- Experience in Medicaid.
- Experience in risk adjustment.
- Experience with data mining and predictive modeling techniques.
-
Generate standard or custom reports summarizing business, financial, or economic data for review by executives, managers, clients, and other stakeholders.
via MATH 491
-
Provide technical support for existing reports, dashboards, or other tools.
via MATH 491
- Document specifications for business intelligence or information technology reports, dashboards, or other outputs.
-
Disseminate information regarding tools, reports, or metadata enhancements.
via MATH 491
-
Analyze competitive market strategies through analysis of related product, market, or share trends.
via MATH 491
These could be filled by an applied project, elective, or internship — see the program page for examples.
What Strategy, Analytics and & Execution in Emerging therapies contributes to Cardinal Health This role supports Cardinal Health by applying advanced analytics, structured problem-solving, and process excellence to drive data-informed decision-making and execution across complex, cross-functio
- Bachelor's degree or equivalent work experience preferred.
- Typically 5-8 years of experience in analytics, strategy, consulting, operations, or related healthcare roles preferred.
- Excellent analytical, organizational, and critical-thinking skills.
- Demonstrated ability to manage complex, cross-functional work independently.
- Strategy, Analytics & Insight
- Uses AI-assisted analytics tools (e.g., Copilot, Gemini, LLM-based tools) to rapidly synthesize large datasets, identify trends, and generate actionable insights.
- Applies prompt engineering and AI-driven workflows to enhance modeling, reporting, and business case development.
- Applies advanced analytical and business judgment to evaluate complex and ambiguous problems, generating actionable insights that inform strategic and operational decisions.
- Benefits: Cardinal Health offers a wide variety of benefits and programs to support health and well-being.
- Medical, dental and vision coverage
- Paid time off plan
- Health savings account (HSA)
-
Generate standard or custom reports summarizing business, financial, or economic data for review by executives, managers, clients, and other stakeholders.
via MATH 491
-
Provide technical support for existing reports, dashboards, or other tools.
via MATH 491
- Document specifications for business intelligence or information technology reports, dashboards, or other outputs.
-
Disseminate information regarding tools, reports, or metadata enhancements.
via MATH 491
-
Analyze competitive market strategies through analysis of related product, market, or share trends.
via MATH 491
These could be filled by an applied project, elective, or internship — see the program page for examples.