Our Opportunity:

We are looking for a Senior Data Scientist or Statistician or Economist with a background in econometric modelling to join the Marketing Science team at Chewy in Boston, MA or Seattle, WA. The team uses Business Economics, Statistics, and Machine Learning techniques to understand and serve the needs of our pet-parents. Developing data-driven marketing solutions, we are an interdisciplinary team of analysts, who are committed to solving business problems using cutting edge technologies and developing data-driven marketing solutions. 

As part of the growing data science team within Marketing Product, Science and Tech team at Chewy, you will have the opportunity to provide structure to the business problems for all things marketing and existing Chewy customers. The problems will range across various stages of the customer lifecycle and marketing levers (product, pricing, promotions, placement and convenience). For these business problems, you will lead/perform the feature and behavior analysis, understand the need and fit of different ML/statistical techniques, develop the best-suited models with business intuition, validate/re-fit those models periodically and employ them at scale. 

As we develop the Customer Development function within the Marketing Analytics team and set up various capabilities, you will have the opportunity to operate or lead as a full-stack data scientist. In that capacity, you will have the opportunity to design and develop the backend ML frameworks, solve business problems, build engineering pipelines to streamline the model development process and launch the decision engines that would help automate the ML-powered business solutions. For such efforts, you will closely work with the data science, analytics, and data engineering teams focused on onsite and offsite marketing. 

What You'll Do:

• Focusing on the incrementality and the value-creation in everything you do, you will closely work the stakeholders within the marketing and merch category teams (Consumables, Hardgoods, Healthcare, etc.). You will transform their ideas, preliminary findings, or analyses, whenever applicable, into machine learning-driven business strategies, programs and actions that would help drive the core objectives 
• For such transformations, you will guide the teams with the design of experiments, measurement, analyses, recommendations, or all. As a data scientist, you will be responsible for making recommendations for experimentation and measurement by researching state-of-art methods, examining, and tuning the current methods with simulations. Also, you will use causal inference methods to bring precision and speed in the decision-making process
• You will be responsible for the full Data Science lifecycle from conception to prototyping, testing, deploying, and measuring the overall business value of the models. In addition, you will periodically develop the model health reports to ensure the integrity of the underlying processes and assumptions. If needed, you will refit the model following the model lifecycle. Using the ML model outputs, you will work with a team of strategic analysts and engineers to triangulate different inputs and optimize the solutions for different business problems
• You will ideate, architect, and build the technical platforms for our algorithmic engines such as Targeting and Product Optimization for Cross-sell/Up-sell/Autoship/Onboarding, etc., Promotion Optimization, Loyalty Program Optimization, etc.
• You will use data to improve how we make decisions and ultimately, enhance customer experience and drive loyalty. You will surface deep insight hidden in our data lakes and provide tactical and strategic guidance on how to act on findings. It will include developing data-science driven customer segmentation (Lifecycle Segments, Value Segments, etc.)
• You will work with the data engineering teams to develop the automated pipelines to perform different stages of the model life cycle (data collection and cleaning, model development and validation, model deployment and scoring, periodic validation and refitting, etc.)

What You'll Need:

• Graduate degree (MS/PhD) in Data Science, Machine Learning, Economics, Statistics, Mathematics, Engineering or related discipline
• 5+ years of professional experience (2+ for PhD) in data science and/or applied economics
• Demonstrated practical knowledge in the areas of machine learning, deep learning, experimentation
• Advanced proficiency in coding and data analysis using Python, SQL, R, SAS, or Scala
• Proven experience in the design and execution of analytical projects.
• Working knowledge of AWS data toolset (Glue, Athena, Sagemaker, Redshift, etc.)
• 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
• Preferably experience of working in CRM data science, analytics, channel marketing channels (Upper/Mid/Lower funnel), lifetime value management, etc.
• Preferably experience of working in the e-commerce industry
• Travel may be required