Senior Data Scientist

WW / WeightWatchers

CA, San Francisco

This job has been expired

WW is looking for candidates to help change people’s lives. We are a global wellness technology company inspiring millions of people to adopt healthy habits for real life. We do this through engaging digital experiences, face-to-face workshops and sustainable programs that encourage people to move more, shift their mindset and eat healthier while enjoying the foods they love. By drawing on over five decades of experience and expertise in behavioral science, we build communities in order to deliver wellness for all.

Role Overview

We are seeking candidates to join a team of highly talented Data Scientists with a primary focus of building data products that improve the lives of WW’s millions of daily active members. The data science team’s applications have an opportunity to interact with members in a myriad of ways, whether it is food, sleep, and fitness tracking, searching for recipes, shopping in our store, or supporting each other in our online coaching and social network. WW is inherently a data product and we can leverage our data—a massive longitudinal dataset across a wealth of touch points and millions of members in different geographies and demographics—to create a more profoundly personalized and impactful experience.

With data science as a key strategic initiative for the organization, the team has been successful in integrating deeply into many areas of the business including product, engineering, marketing, finance and e-commerce. The WW data science team is a separate entity from the analytics and data engineering teams, freeing up the data scientists for a singular focus: building awesome data products. Data science products often include scalable and effective end-to-end solutions for production models, recommenders, and optimization systems.

Key Responsibilities

  • Partner with stakeholders across the organization to identify high-impact opportunities to leverage our extensive data to better serve our members.
  • Lead the development of predictive and other machine-learned models to enhance user engagement and experience.
  • Perform and advise on exploratory and targeted analyses to understand the data, the problem, and to generate insights, such as novel features, that can be fed into our models.
  • Manage end-to-end workflow of projects including: delegating tasks with the rest of the team, communicating with our consumers and partners in dev and product, and implementing and shipping production-level code and deployments.
  • Develop novel deployment and scaling strategies to more effectively run DS services.
  • Explore and assess utility and potential of additional data sources, APIs, and methods (spanning areas such as statistics, deep learning, and natural language processing).
  • Motivate and mentor other data scientists to grow their skills and careers.
  • Develop a deep expertise in one or more areas, becoming a domain expert on the team.
  • Peer review other data scientists’ contributions.
  • Making substantial contributions to our open sourced projects and contributing to external open source projects to further the team’s impact on the DS world

Job Requirements

  • 3+ years of experience building and implementing machine-learned models in industry, ideally dealing with problems relevant to behavior change, community, product, and/or marketing.
  • Ability to scope and (self-)manage machine learning modeling projects.
  • Experience leading end-to-end data science projects from initial scoping and development to deployment
  • Expert knowledge of Python and SQL for large-scale data analysis and modeling (e.g. sklearn, numpy, pandas).
  • Deep experience with advanced modeling techniques, such as collaborative filtering and content-based recommenders, matrix factorization, time series analysis, classifiers, natural language processing, and ensemble methods.
  • Experience in deep learning for images or text (, PyTorch, Tensorflow, huggingface)
  • Expert with software engineering best principles: git workflow, testing, and code review practices.
  • Experience with Google Cloud Platform (Dataflow, Beam, BigQuery) and other big data technologies a plus.
  • Degree (B.S.) in data science, statistics, or a related quantitative discipline. Advanced degree (Ph.D./MS) is preferred.
  • Self-motivated, results oriented, enthusiastic, and a creative thinker.

At WW, it is our priority to cultivate a diverse and inclusive workplace. We are committed as individuals, as an organization, and as fellow humans, to advocate for and support our employees, our members, and our communities. We are proud to be an equal opportunity employer and we do not discriminate on the basis of sex, race, color, creed, national origin, marital status, age, religion, sexual orientation, gender identity, gender expression, veteran status, or disability.