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Full Time Data Science Analytics Jobs (NOW HIRING)

Adobe

Director, Data Science & Analytics

New York, NY · On-site

We are seeking a world-class Director of Data Science & Analytics to be the analytical engine behind Firefly's creator growth strategy within the Creator org. You will work at the intersection of AI ...

Adobe

Director, Data Science & Analytics

San Jose, CA · On-site

We are seeking a world-class Director of Data Science & Analytics to be the analytical engine behind Firefly's creator growth strategy within the Creator org. You will work at the intersection of AI ...

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How much do full time data science analytics jobs pay per year?

As of Jun 7, 2026, the average yearly pay for full time data science analytics in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is the difference between Full Time Data Science Analytics vs Data Analyst?

AspectFull Time Data Science AnalyticsData Analyst
Required CredentialsBachelor's or Master's in Data Science, Statistics, or related fieldsBachelor's in Statistics, Mathematics, or related fields
Work EnvironmentCross-functional teams, often in tech or finance industriesBusiness units, marketing, finance departments
Employer & Industry UsageTech companies, finance, healthcare, consultingRetail, marketing, finance, healthcare
Common Search & ComparisonYesYes

Full Time Data Science Analytics roles typically require advanced degrees and involve building predictive models and machine learning algorithms, often in tech-driven industries. Data Analysts focus on interpreting data, creating reports, and supporting decision-making with descriptive analytics. While both roles analyze data, Data Science Analytics emphasizes predictive and prescriptive insights, whereas Data Analysts focus on historical data analysis.

More about Full Time Data Science Analytics jobs
What cities are hiring for Full Time Data Science Analytics jobs? Cities with the most Full Time Data Science Analytics job openings:
What are the most commonly searched types of Data Science Analytics jobs? The most popular types of Data Science Analytics jobs are:
What job categories do people searching Full Time Data Science Analytics jobs look for? The top searched job categories for Full Time Data Science Analytics jobs are:
Full Time Data Science Analytics jobs near you
Infographic showing various Full Time Data Science Analytics job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, 74% Full Time, 20% Part Time, and 5% Contract. Highlights an 74% Physical, 3% Hybrid, and 23% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.
Principal, Data Science & Analytics

Principal, Data Science & Analytics

Microsoft

Redmond, WA • On-site

Full-time

Posted yesterday

Microsoft rating

8.6

Company rating: 8.6 out of 10

Based on 125 frontline employees who took The Breakroom Quiz

47th of 186 rated software companies

Job description

Overview
Microsoft AI (MAI) builds an integrated consumer AI ecosystem across search, browsing, and content, focused on delivering trustworthy, scalable experiences with durable user and business value. The MAI Ecosystem Data Science Team owns MAI-wide metrics, shared measurement systems, and experimentation frameworks to enable consistent, high-confidence decisions and optimize MAI-level outcomes.
We are seeking a Principal, Data Science & Analytics for ecosystem data science to own cross product measurement strategy, partner across product and business teams, and uphold a high bar for metric quality, statistical rigor, and data driven leadership.
We are looking for high-energy Data Scientist, creative modeling geeks who are willing to work in a dynamic environment to solve real life day to day problems, leveraging data science techniques. You will enjoy and be successful in this role if you are curious and willing to challenge the status quo and come up with data driven solutions to ambiguous problems.
Microsoft's mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50- mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.
Responsibilities
As a Principal, Data Science and Analytics in the team, your major responsibilities include:
  • Leadership: Mentor data scientists and align work with MAI ecosystem goals, driving technical excellence, innovation, and cross-team collaboration.
  • Data Strategy & Execution: Develop ecosystem data strategies for marketplace and system performance, including standardized data collection, analysis, reporting, and interpretation; validate analytical approaches and results.
  • Advanced Analytics & Measurement: Apply machine learning, statistical modeling, data mining, and experimentation to large datasets; define and deliver metrics that accurately measure user and business value across products and marketplace components.
  • Experimental Design & Implementation: Design and execute experiments across user and demand dimensions; translate strategy into clear, actionable, and measurable plans, sharing progress and results with stakeholders.
  • Collaboration: Partner closely with product, program management, engineering, and business teams to integrate data science solutions into shared platforms and marketplace operations.
  • Performance Optimization: Identify cross-team opportunities for product and process improvement; implement data-driven solutions to improve efficiency, reliability, and user experience.
  • Influence & Decision-Making: Engage stakeholders with clear, compelling, and actionable insights; make independent decisions for the team and handle complex tradeoffs to drive product and service improvements.
  • Technical & Operational Leadership: Develop and standardize processes for data acquisition, quality, and operationalizing ML models; provide expert review of analysis and modeling; lead adoption of new tools and technologies to improve availability, reliability, efficiency, and performance.
  • Standards & Trusted Advisory: Establish and uphold standards, policies, and best practices for high-quality, efficient, and extensible code; influence business, customer, and solution strategy with a strong customer focus; act as a trusted advisor across the ecosystem.

Qualifications
Required Qualifications:
  • Doctorate 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 Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ 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 10+ 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 8+ 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 10+ 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 12+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
    • OR equivalent experience.

#MicrosoftAI
Data Science IC5 - The typical base pay range for this role across the U.S. is USD $139,900 - $274,800 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 $188,000 - $304,200 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.

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About Microsoft

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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

Social media

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