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Senior Agriculture Data Science Jobs (NOW HIRING)

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Senior Manager, Data Science

Foster City, CA · On-site

As a Senior Manager Data Scientist, you will be an integral part of a multi-functional development team inventing, designing, building, and testing products that reach a truly global customer base.

Chewy

Director, Data Science

Bellevue, WA · On-site

You will lead a team of data scientists building the intelligence layer across the full advertising ... Represent Ads science to senior leadership--translating complex work into clear strategy, tradeoffs ...

Chewy

Director, Data Science

Bellevue, WA · On-site

You will lead a team of data scientists building the intelligence layer across the full advertising ... Represent Ads science to senior leadership-translating complex work into clear strategy, tradeoffs ...

AbbVie

Senior Manager, Data Science

North Chicago, IL · On-site

$142K - $208K/yr

Senior Manager, Data Science, AbbVie Inc., North Chicago, IL (Hybrid (onsite 3 days a week/ 2 days WFH)). Key Responsibilities * Deliver biomarker analysis expertise for clinical studies. * Ensure ...

AbbVie

Senior Manager, Data Science

North Chicago, IL · Hybrid

$142K - $208K/yr

Senior Manager, Data Science, AbbVie Inc., North Chicago, IL (Hybrid (onsite 3 days a week/ 2 days WFH)). Key Responsibilities * Deliver biomarker analysis expertise for clinical studies. * Ensure ...

Dell, Inc.

Senior Advisor, Data Science

Round Rock, TX · On-site

$127K - $127K/yr

Senior Advisor, Data Science Data Science Senior Advisor (Taxonomy, Ontology, and Governance) Data Science is all about breaking new ground to enable businesses to answer their most urgent questions.

Dell, Inc.

Senior Advisor, Data Science

Round Rock, TX · On-site

$127K - $127K/yr

Senior Advisor, Data Science Data Science Senior Advisor (Taxonomy, Ontology, and Governance) Data Science is all about breaking new ground to enable businesses to answer their most urgent questions.

Tulk LLC

Data Science SME Senior

Fort Belvoir, VA · On-site

Data Science SME Senior TULK supports U.S. national security customers with cleared experts who understand the mission, the tradecraft, and the people who have to make decisions with imperfect ...

Bunge North America

Data Scientist

Chesterfield, MO · On-site +1

... senior leadership, traders, and business units, supporting informed decision-making and global risk ... Minimum MS degree in Economics, Agricultural Economics, Statistics, Computer Science, Quantitative ...

Bunge

Data Scientist

Chesterfield, MO · On-site

... senior leadership, traders, and business units, supporting informed decision-making and global risk ... Agricultural Economics, Statistics, Computer Science, Quantitative Finance, Business Analytics, or ...

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Senior Agriculture Data Science information

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$16

$56

$81

How much do senior agriculture data science jobs pay per hour?

As of Sep 2, 2026, the average hourly pay for senior agriculture data science in the United States is $56.81, according to ZipRecruiter salary data. Most workers in this role earn between $46.63 and $67.31 per hour, depending on experience, location, and employer.

What is the difference between Senior Agriculture Data Science vs Agriculture Data Scientist?

AspectSenior Agriculture Data ScienceAgriculture Data Scientist
Required CredentialsBachelor's/Master's in Data Science, Agriculture, or related fields; experience preferredBachelor's/Master's in Data Science, Agriculture, or related fields; entry to mid-level experience
Work EnvironmentResearch labs, agricultural companies, tech firmsResearch institutions, agricultural firms, startups
Employer & Industry UsageUsed in organizations seeking advanced data analysis and leadershipUsed in organizations focusing on data analysis and modeling in agriculture

Senior Agriculture Data Science roles typically require more experience, leadership, and advanced skills compared to Agriculture Data Scientists. While both roles involve data analysis in agriculture, senior positions often include project management and strategic responsibilities, whereas data scientists focus on technical analysis and modeling.

What cities are hiring for Senior Agriculture Data Science jobs?

Cities with the most Senior Agriculture Data Science job openings:

What are the most commonly searched types of Agriculture Data Science jobs?

The most popular types of Agriculture Data Science jobs are:

What states have the most Senior Agriculture Data Science jobs?

States with the most job openings for Senior Agriculture Data Science jobs include:

Senior Agriculture Data Science jobs near you

Senior Data Scientist - Media Data Science & Analytics

Microsoft

Redmond, WA • On-site

Full-time

Posted 29 days ago

Microsoft rating

8.5

Company rating: 8.5 out of 10

Based on 132 frontline employees who took The Breakroom Quiz

81st of 247 rated software companies

Job description

Overview
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.

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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

Social media

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