Data Scientist (Marketing)

As a Research Data Scientist I you will help advance measurement and analytics in TV viewing and advertising. You will work on audience measurement, attribution and lift analytics, and creative testing — taking prototypes from research into production-ready solutions in collaboration with product and engineering teams.

• Conduct in-depth data analysis and exploratory data work on large viewing and demographic datasets to generate actionable insights.
• Build and validate statistical and machine learning models for measurement, attribution, and lift analysis.
• Develop, train, and deploy ML models using best practices for reproducibility, testing, and monitoring.
• Design and implement efficient data pipelines to ingest, process, and transform data from multiple sources (ETL/ELT).
• Prototype novel methodologies and collaborate with cross-functional product and engineering teams to scale solutions.
• Communicate technical results clearly to stakeholders and help translate analytics into product opportunities.

• Bachelor’s degree in mathematics, statistics, computer science, economics, physics, or another quantitative discipline (master’s preferred but not required).
• 1–3 years of professional experience in data science, applied statistics, or modeling.
• Strong foundation in statistics, experimental design, causal inference, or applied machine learning.
• Proven ability to analyze high-dimensional datasets and produce interpretable results.
• Comfortable working in a hybrid environment and collaborating with engineers and product managers.

• Proficient in Python and/or R for data analysis and model development.
• Strong SQL skills for data extraction, transformation, and validation.
• Experience building or deploying models in production, or working with data pipelines (Spark, Airflow, dbt, etc.).
• Familiarity with advertising measurement, TV viewing data, attribution, lift testing, or related media analytics.
• Excellent written and verbal communication skills; ability to present technical concepts to non-technical stakeholders.
• Pragmatic, collaborative, and detail-oriented with strong critical thinking skills.

• Target cash compensation range: $95,950 - $106,000 USD annually. This includes base salary and any applicable variable/bonus components where eligible.
• Eligible employees may participate in equity plans, standard benefits, and other rewards as offered by the confidential client. Individual packages depend on experience, role, and location.
• The confidential client is committed to providing competitive, market-informed compensation.

• Role is listed as telecommute / hybrid depending on location and business needs. Candidates local to Bellevue, WA (or other nearby offices) may be expected to work on-site part-time (commonly 1–3 days/week). Fully remote arrangements may be considered depending on role responsibilities and location.
• Exact schedule and office expectations will be discussed during the interview process.

• Applicants must be currently authorized to work in the United States. The confidential client is not able to sponsor or take over sponsorship of an employment visa for this position at this time.
• If you require a reasonable accommodation due to a disability during the application or hiring process, please request assistance and the confidential client will work with you to provide appropriate support.

We use a combination of resume review, technical interviews, and practical assessments to evaluate skills in data analysis, modeling, and communication. AI tools may be used to help screen applications for relevant keywords and qualifications, but human reviewers make final hiring decisions.

CareerTakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process,  AI tools may be used  to assist with application review or resume screening. These tools  do not replace human decision-making . Final hiring decisions are made by people.

If you have questions about how your data is used, please contact us directly.