We are looking for a Director of Data Science to join the Marketing Science team at Chewy in Boston, MA. 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.
This is a leadership position that will have exposure across the entire business, influencing the vision and implementation of marketing strategies for customer acquisition and development. As part of the growing data science team within the broader 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. In this role, the problems may range across various stages of the customer lifecycle (Acquisition, CRM), marketing channels (TV, DM, Digital Channels, etc.), marketing levers (product, pricing, promotions, placement and convenience) and business economics (Spend Optimization, Budgeting and Planning). As a leader, you will have the opportunity to develop the frameworks and roadmaps to solve these problems in an efficient way, work with the stakeholders to align on priorities, and closely work your team to build the best-fitted data-driven solutions. These solutions will include (but will not be limited to) using statistical techniques to design experiments, measuring long term impact of those experiments, developing state of the art ML driven solutions, building optimization frameworks, etc. In this role, you will also closely work with the team of data engineers, product management and software developers to build the backend for ML frameworks and automate those solutions.
What You'll Do:
- Hire, develop and lead a team of data scientists, statisticians and analysts
- Identify and manage priorities within the context of overall Chewy objectives, and work with colleagues in data science and engineering to drive the best practices in development, testing, and production of models at scale
- Establish strong working relationship at all organizational levels across different functional teams
- 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, and recommendations. 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 manage the data science practices for business problems such as media mix modeling, cross-channel spend optimization, multi touch attribution, propensity, net lift, causal inference, structural equation modeling, etc. For such models, 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. Also, you will manage the model health and the integrity of the underlying processes and assumptions. If needed, you will refit the model following the model lifecycle
- You will ideate, architect, and build the technical platforms for our algorithmic engines such as Targeting, Spend and Product Optimization
- 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 the insights.
- 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
- 8+ years of professional experience (5+ 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 through structural thinking in ambiguous problem spaces
- 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 cross-channel spend optimization, budgeting, attribution, CRM data science, and LTV management.
- Preferably experience of working in the e-commerce industry
- Position may require travel