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 2026-06-05.
Scraper last re-confirmed a WA posting 2026-06-05 11:59.
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.