Chewy is looking for a Data Scientist – ML Ops, Statistician or Economist with a background in marketing measurement to join the Measurement Science team at Chewy. The team uses Business Economics, Statistics and Machine Learning techniques to understand and serve the needs of our pet-parents. The team is committed to developing data-driven 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 ML 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.
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 could lead the design of experiments across marketing channels and platforms.
What You'll Do:
- 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 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.
- 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:
- Bachelors’ degree with 5+ years, Master's degree with 3+ years or PhD with 2+ years of relevant experience in Science, Economics, Statistics, Mathematics, Engineering, or related discipline
- Ability to lead end-to-end model development and work independently with limited coaching
- Proficiency in Python, R and SQL and open-source machine learning and analytics packages
- Hands-on working experience in areas of machine learning, experimentation, causal inference, developing marketing mix modeling, time series modeling, forecasting, etc. is preferred
- Experience with AWS data toolset (Athena, Sagemaker, Redshift, etc.) or similar technologies is preferred
- Experience in attribution, spend optimization, incrementality testing, etc.is nice to have.
- 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. is preferred
- Experience of translating ambiguous customer requirements into clear problem definitions and delivering them
- Excellent verbal and written communication skills. Able to explain details of complex concepts to non-expert stakeholders in a simple understandable way
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]