Chewy is looking for a Data Scientist or Statistician or Economist with a background in marketing measurement to join the Measurement Science team at Chewy. The team is committed to developing data-drive solutions, advancing measurement capabilities, building optimization frameworks, establishing best practices, and identifying growth opportunities across marketing channels, using methodologies such as marketing mix modeling (MMM), testing / experimentation, attribution, causal Inference, forecasting, 3rd party solutions, etc.
As we grow the Measurement Science function within the Marketing Science & Operations team and set up various capabilities from ground up, you will have the opportunity to operate or lead as a full-stack data scientist. In that capacity, you will have the opportunity to develop backend modeling frameworks, solve business problems, design experiments, build pipelines to streamline model development, partner with media partners and 3rd-party vendors to identify and implement new capabilities and best measurement practices, etc. For such efforts, you have chance to work closely with business partners, Analytics, Product and Tech teams, as well as external parties.
Committed to value-creation, you will work with marketing and finance stakeholders as a thought partner and guide them in their decision-making process using data and models as your north star. You will develop models and deliver insights to drastically improve how we plan and optimize our marketing efforts, drive budget allocation and spend optimization to maximize the overall value for Chewy, and identify areas and opportunities to grow our business through data and learning. Supporting company’s growth agendas with speed and accuracy, you will also have the opportunity to lead the design of experiments across marketing channels and platforms.
What You'll Do:
- Build, maintain and evolve marketing measurement framework (e.g., marketing mix model, testing / experimentation, attribution, causal inference, etc.)
- Own and manage end-to-end modeling development processes, e.g., translate strategic business questions into modeling, analysis and optimization frameworks to inform business and financial decisions; manage data gathering, validation, preprocessing, model development, calibration, and evaluation; interpret and validate model outputs and extract insights, communicate with business partners, and incorporate feedback to iterate and improve results and insights.
- Develop and evolve marketing mix modeling (MMM) to evaluate the effectiveness and efficiency of marketing channels, platforms, tactics, etc.
- Develop and evolve scenario planning optimization tools and frameworks to inform budget planning and spend optimization, and forecast business outcomes.
- Develop testing hypotheses, design experiments (e.g., multivariate, A/B, geo), size opportunity cost, implement tests/experiments, analyze results, summarize findings, and make recommendations for next steps. Leverage learnings to calibrate models and inform growth opportunities for business.
- Build causal measurement frameworks or models to evaluate and measure impact and efficiency.
- Identify, evaluate or build optimal attribution framework or model for cross-channel and in-channel attribution.
- Prepare media optimization scenarios to inform media plans and spend across media channels, forecast performance, and identify areas for efficiency improvements.
- Explain complex modeling approaches in simple terms; Develop compelling narratives that connect modeling results with marketing problems.
- Develop reports, data visualizations and presentations; document and track model performance; communicate actionable insights or business impact to stakeholders.
What you'll need:
- Master’s degree in Statistics, Mathematics, Economics, Physics, Psychology, Computer Science, Engineering, or related quantitative discipline is required; PhD is preferred.
- Practical hands-on working experience in developing marketing mix modeling.
- Demonstrated practical knowledge in the areas such as time series modeling, forecasting, experimentation, causal inference, etc. to answer challenging and impactful questions
- Experience in attribution, spend optimization, incrementality testing, etc.
- Ability to lead end-to-end model development and work independently with limited coaching.
- Proficiency in Python, R and SQL.
- Preferably experience in marketing analytics related fields, or domain knowledge familiar with marketing channels, KPIs, marketing platforms (e.g., Google, Facebook), marketing tools such as Google Analytics, Ads Data Hub, etc.
If you have a disability under the Americans with Disabilities Act or similar law, or you require a religious accommodation, and you wish to discuss potential accommodations related to applying for employment at Chewy, please contact [email protected]