Our Opportunity:

Chewy is looking for a Data Scientist or Machine Learning Scientist with a background in econometric modelling to join the Autoship Data Science team at Chewy. The team uses Business Economics, Statistics, and Machine Learning techniques to understand and serve the needs of our pet-parents. Developing data-driven customer solutions, we are an interdisciplinary team of analysts, who are committed to solving business problems using cutting edge technologies.

As part of the growing Autoship Data Science team, you will have ample opportunities to provide structures to numerous business problems for all things marketing and existing Chewy customers. The problems will range across various stages of the customer lifecycle (acquisition, growth, management, and retention) and marketing levers (product, pricing, promotions, placement, and convenience). With direct exposure to the cross-functional stakeholders, you will have a unique opportunity to formulate analytical solutions for these problems from scratch and develop customer-centric products for efficiency using experimentation, data science and analytics. For such efforts, you will closely work with the data science, analytics, product, and data engineering teams focused on Autoship business functions.  

What You'll Do:

• You will be responsible for the full Machine Learning 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. 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
• Focusing on the incrementality and the value-creation in everything you do, you will closely work with the stakeholders within marketing. You will transform their ideas, preliminary findings, or analyses, whenever applicable, into set of features to guide your machine models 
• For such transformations, you will guide the teams with the design of experiments, measurement, analyses, recommendations, or all. With partnership from Analytics, 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 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, Likelihood Models etc.)
• You will work with the data engineering teams to develop the automated pipelines to perform different stages of the model life cycle

What You'll Need:

• Bachelors’ degree with 5+ years, Master's degree with 3+ years or PhD with 2+ years of relevant experience in Machine Learning, Data Science, Economics, Statistics, Mathematics, Engineering, or related discipline
• Demonstrated practical knowledge and hands-on experience in the areas of machine learning, deep learning, experimentation, especially track record of developing propensity, uplift/causal inference, product recommendation models, managing the model life cycle and partnering with the ML engineering and product teams to scale the efforts.
• Coding ability in a scripting language such as Python, R, Matlab, SQL, SAS or STATA
• Working knowledge of AWS data toolset (Glue, Athena, Sagemaker, Redshift, etc.)
• Experience of translating complex business problems into its MECE components and prioritizing different components on their values and impacts
• 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 subscription-based model, attribution, A/B testing optimization and CRM data science
• Preferably experience of working in the e-commerce industry
• You enjoy working in a team of highly engaged individuals, and you have a passion for data science and KPIs, but also for delivering analysis of the highest quality
• Proven experience in identifying opportunities for business improvement and defining and measuring the success of those initiatives

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