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Senior Optum Data Science information
See salary details
$25K - $37.6K
14% of jobs
$43.9K is the 25th percentile. Wages below this are outliers.
$37.6K - $50.2K
22% of jobs
$50.2K - $62.8K
9% of jobs
The median wage is $71.8K / yr.
$62.8K - $75.4K
7% of jobs
$75.4K - $88K
12% of jobs
$98.1K is the 75th percentile. Wages above this are outliers.
$88K - $100.5K
14% of jobs
$100.5K - $113.1K
9% of jobs
$113.1K - $125.7K
4% of jobs
$125.7K - $138.3K
3% of jobs
$138.3K - $150.9K
4% of jobs
$150.9K - $163.5K
2% of jobs
$25K
$80.3K
$163.5K
How much do senior optum data science jobs pay per year?
What is the difference between Senior Optum Data Science vs Data Analyst?
| Aspect | Senior Optum Data Science | Data Analyst |
|---|---|---|
| Required Credentials | Advanced degree in Data Science, Statistics, or related field; experience with machine learning | Bachelor's degree in Data Analysis, Statistics, or related field; some experience with data tools |
| Work Environment | Healthcare analytics, cross-functional teams, complex data modeling | Data reporting, visualization, basic analysis in various industries |
| Employer & Industry Usage | Optum/UnitedHealth Group, healthcare industry | Various industries including healthcare, finance, retail |
Senior Optum Data Scientists focus on advanced analytics, machine learning, and healthcare-specific data challenges within Optum. Data Analysts typically handle data reporting, visualization, and basic analysis across multiple industries. The roles differ mainly in complexity, required skills, and industry focus, with Senior Data Scientists engaging in more technical and strategic tasks.
What cities are hiring for Senior Optum Data Science jobs?
Cities with the most Senior Optum Data Science job openings:
What are the most commonly searched types of Optum Data Science jobs?
The most popular types of Optum Data Science jobs are:
What states have the most Senior Optum Data Science jobs?
States with the most job openings for Senior Optum Data Science jobs include:
What job categories do people searching Senior Optum Data Science jobs look for?
The top searched job categories for Senior Optum Data Science jobs are:

Senior Data Scientist - Media Data Science & Analytics
Redmond, WA • On-site
8.5
Based on 132 frontline employees who took The Breakroom Quiz
80th of 246 rated software companies
Great coworkers
People enjoy working here
Good employer
Paid breaks
Recommended by parents
Full-time
Posted 27 days ago
Job description
We're building a Frontier Marketing organization where the Media Data Science & Analytics team leads the way in transforming how Microsoft measures, analyzes, and optimizes media investments. Our team blends advanced analytics, experimentation, and AI-powered insights to drive smarter decision-making and measurable business outcomes across paid media and owned digital properties.
We operate with agility, prioritize outcomes over activity, and embrace rapid learning loops to unlock deeper audience understanding, maximize campaign impact, and accelerate innovation in media strategy.
To support this transformation, we are seeking a Senior Data Scientist to help us measure the incremental impact of advertising spend and use that to help our media planning partners optimize media campaigns.
Marketing data science is inherently challenging: data is often observational, incomplete, biased, or limited in scale, and outcomes unfold over time across complex systems. The successful candidate will be someone who can apply rigorous causal methods, exercise sound statistical judgment, and translate uncertainty into actionable insights that inform high-stakes investment decisions.
Responsibilities
Causal Measurement & Business Impact
- Design and apply causal inference approaches (e.g., quasi-experimental methods, incrementality testing, observational analysis) to estimate the true impact of media investments in settings where randomized experiments may be limited or infeasible.
- Evaluate the effectiveness of marketing strategies while explicitly accounting for data limitations, confounding, selection bias, and uncertainty.
- Translate complex causal findings into clear, decision-oriented narratives for senior marketing and business stakeholders.
Modeling, Statistics & Analysis
- Apply advanced statistical techniques and machine learning where appropriate, with a bias toward interpretability and causal validity over purely predictive performance.
- Balance methodological rigor with pragmatism, selecting approaches that are fit for purpose given the data and business context.
- Write high-quality analytical code (Python, SQL) to support reproducible research, exploratory analysis, and ongoing measurement efforts.
- Identify opportunities to improve measurement approaches, challenge existing assumptions, and introduce best practices grounded in both academic research and industry experience.
Data Understanding & Stewardship
- Prepare, validate, and analyze complex marketing datasets, identifying data quality issues, structural changes, and limitations that materially affect inference.
- Communicate data risks, constraints, and implications proactively to senior partners, ensuring conclusions are appropriately scoped and caveated.
- Uphold high standards for data ethics, privacy, and responsible use, with careful attention to how data is collected, modeled, and interpreted.
What Success Looks Like
- Media investment decisions are better informed by clear, credible causal insights rather than surface-level correlations.
- Stakeholders understand not only what the data suggests, but how confident we are and why.
- Analytical recommendations appropriately reflect data constraints and uncertainty, earning trust through transparency and rigor.
- The team consistently applies causal thinking to difficult, ambiguous marketing problems, even when the data is imperfect.
Qualifications
Required/Minimum Qualifications
- Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience.
Preferred Qualifications
- Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 6+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 8+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience.
- 5+ years' experience building ML models.
- 5+ years' experience writing SQL to analyze data.
- 5+ years' experience writing code in Python.
- 3+ years' communicating complex technical concepts to non-technical partner teams.
- 1+ years' experience performing causal inference
- 1+ years' experience with media / marketing data science
Data Science IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $160,200 - $261,000 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.
About Microsoft
Sourced by ZipRecruiter
Our infrastructure is comprised of a large global portfolio of more than 100 datacenters and 1 million servers. Our foundation is built upon and managed by a team of subject matter experts working to support services for more than 1 billion customers and 20 million businesses in over 90 countries worldwide. With environmental sustainability and optimization at the forefront of our datacenter design and operations, we continue to grow and evolve as we meet the ever-changing business demands that hold Microsoft as a world-class cloud provider.
Industry
Computer and computer peripheral equipment and software wholesalers
Company size
10,000+ Employees
Headquarters location
Redmond, WA, US
Year founded
1975
Website
What Microsoft employees say
Pay
Benefits
Hours and flexibility
Workplace
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