Senior Data Scientist

Dale Workforce Solutions; United States; On-site; USD 120,000 - 170,000; Full time

Job summary

Dale Workforce Solutions seeks a Senior Data Scientist to join the Data Strategy & Analytics team. You will design and execute measurement solutions including incrementality tests, media mix models, and causal analyses, translating results into actionable recommendations.

Collaborate across Data Strategy, media, and client services to tackle complex measurement challenges, handling large marketing datasets and communicating findings and limitations to both technical and non-technical audiences.

Qualifications

• Master's degree in Statistics, Economics, Data Science, Computer Science, Engineering, or another quantitative discipline preferred or B.S. + 5 years of relevant experience.
• Strong programming skills in Python, R, & SQL.
• Hands-on experience designing and analyzing incrementality tests (geo holdouts, matched-market tests, synthetic controls, or randomized experiments).
• Hands-on experience building, validating, and interpreting media mix models.
• Deep understanding of statistical modeling, causal inference, experimental design, and time-series methods.
• Ability to evaluate methodological tradeoffs and select approaches based on data and business needs.
• Ability to work independently on ambiguous problems while collaborating with cross-functional teams.

Responsibilities

• Partner with Data Strategy, media, and client teams to translate business questions into testable measurement plans.
• Design and analyze incrementality tests, including geo-based experiments and other causal approaches.
• Build, validate, and interpret media mix models to estimate channel contribution and efficiency.
• Develop measurement approaches for upper-funnel and brand media and link to lower-funnel outcomes.
• Conduct power analyses, feasibility assessments, sensitivity analyses, and model diagnostics.
• Work with large multi-source datasets, identify data quality issues and measurement gaps.
• Turn analytical findings into practical recommendations for media planning and testing strategies.
• Apply advanced analytics methods like predictive and propensity modeling to broader client questions.
• Mentor junior data scientists and contribute to shared measurement standards and best practices.

Skills

Incrementality testing

MMM (Media Mix Modeling)

Causal inference

Statistical modeling

Experimental design

Time-series methods

Independent work

Education

Master's or PhD in Statistics, Economics, Data Science, CS, Engineering, or related quantitative field

Tools

Python

R

SQL

PyMC

Job description

• Prior experience personally designing and analyzing incrementality tests
• Prior experience personally building, validating, and interpreting MMMs

The Role

We are looking for a Senior Data Scientist to join our Data Strategy & Analytics team and help clients understand the incremental impact of their marketing investments. In this role, you will design and execute rigorous measurement solutions, including incrementality tests, media mix models, and causal analysis. and translate the results into clear, actionable recommendations.

You will partner with Data Strategy, media, client service, and analytics teams to solve complex measurement challenges across channels and funnel stages. You will work directly with large, imperfect marketing datasets, select the right methodology for each business question, and communicate both the findings and their limitations to technical and non-technical audiences.

The ideal candidate has hands-on experience with incrementality testing and media mix modeling, along with a strong understanding of digital and upper-funnel media measurement. You should be comfortable evaluating channels such as CTV, video, audio, OOH, paid social, and other brand investments where last-touch attribution is incomplete. You will also help strengthen our measurement approaches and guide junior & on-level data scientists in sound experimental and modeling practices.

You Will Be

• Partnering with Data Strategy, media, and client teams to translate business questions into clear, testable measurement plans
• Designing and analyzing incrementality tests, including geo-based experiments, holdouts, matched-market tests, and other causal inference approaches
• Building, validating, and interpreting media mix models to estimate channel contribution, efficiency, saturation, and diminishing returns
• Developing measurement approaches for upper-funnel and brand media, including its direct impact and influence on lower-funnel outcomes
• Conducting power analyses, test feasibility assessments, sensitivity analyses, and model diagnostics to ensure findings are statistically credible
• Working with large, multi-source marketing datasets; identifying data quality issues, measurement gaps, and implications for analysis
• Turning analytical findings into practical recommendations for media planning, optimization, and future testing
• Applying complementary advanced analytics methods - including predictive modeling, propensity modeling, segmentation, and forecasting - to solve broader client and media strategy questions
• Guiding and mentoring junior data scientists and contributing to shared measurement standards, code, and best practices

You Must Have

• Education: Master's degree in Statistics, Economics, Data Science, Computer Science, Engineering, or another quantitative discipline preferred or B.S. + 5 years of relevant experience
• Strong programming skills in Python, R, & SQL
• Hands-on experience designing and analyzing incrementality tests, such as geo holdouts, matched-market tests, synthetic controls or holdouts, or randomized experiments
• Hands-on experience building, validating, and interpreting media mix models
• A deep understanding of statistical modeling, causal inference, experimental design, and time-series methods
• Ability to evaluate methodological tradeoffs, challenge weak assumptions, and select approaches appropriate to the available data and business decision
• Ability to work independently on ambiguous problems while collaborating closely with cross-functional teams

Nice to Have

• Experience with Bayesian modeling frameworks such as PyMC or similar tools
• Experience calibrating or validating MMM results with incrementality tests, or integrating multiple measurement methods into a unified recommendation
• Experience with brand measurement, awareness studies, retail or offline sales data, or multi-outcome/funnel modeling