Manager, Data Science

Weight Watchers International   •  

New York, NY

Industry: Consulting


5 - 7 years

Posted 333 days ago

Manager, Data Science

Weight Watchers is a 50+year-old brand, with a massive amount of data at our fingertips that is unique to its business: from verified weight loss patterns, to behavioral habits across multiple Program iterations, to rich socialnetworkinteractions on multiple geographies and demographics - and many more.


We are committed to delivering the best possible experience for our members while constantly innovating on all our channels of delivery, in the physical world through our meeting rooms and the digital world through our apps and services. We know that in order to offer best-in-class service, we need to make the WW experience a truly personalized one to each member, while maintaining scientific accuracy and efficacy on our members’ weight loss journeys. And we know the only way to get there is through the enablement from a solid Data Science Practice.

Role overview

We are looking for a Manager to lead our Data Science team, and help take our capabilities to the next level, leveraging some exciting personalization opportunities, spanning across our private social network (Connect) to food recommendation engines, and more. The ideal candidate will bring a sense of curiosity to find opportunities for our business based on our data - the possibilities are limitless!


Our Data Science Practice also benefits from advisory council from Professors at Columbia University, and an influx of new talent from their Operations Research department.

Key responsibilities

  • Manage the team of Data Scientists in their day-to-day operations, modeling reviews, and approaches around data problem solving
  • Partner with Analytics and stakeholders across the organization to identify high-impact opportunities to leverage our extensive data to better serve our users
  • Assess the potential usefulness and validity of new statistical approaches and data sources
  • Help enable the team to build complex predictive models to substantially improve and continuously optimize user engagement
  • Reach across multiple functions, such as Product Management and Data Engineering, to implement the models into production and to monitor their performance
  • Develop rigorous data science models to aggregate inconsistent real-time signals into strong predictors of market trends
  • Motivate and mentor other data scientists to grow their skills and careers
  • Hiring world-class Data Scientists and developing team-wide best practices
  • Provide clear directions and priority guidance to the Data Scientists on a day-to-day basis

Experience required

  • Advanced Degree (Ph.D./MS) in Statistics or a related quantitative discipline.
  • Experience managing, hiring and coaching a team of Data Scientists
  • Experience in the consumer internet space, a bridge between physical and digitalexperiences a plus
  • 5+ years of experience building and implementing complex models in a fast-paced corporate environment, ideally dealing with problems relevant to behavior change, community, product, and/or marketing.
  • Experience with advanced modeling techniques, such as collaborative filtering, matrix factorization, time series analysis, and mixed-effect models, and learning techniques such as boosting and random forests
  • Expert knowledge of R/Python, and SQL, or similar industry standard tools used for large-scale data analysis and modeling
  • Experience with Machine Learning and Big Datatechnologies, Deep Learning a plus
  • Experience with Google Cloud Platform (Dataflow, Beam, BigQuery, Tensorflow) a plus
  • Self-motivated, results oriented, enthusiastic, and a creative thinker
  • Strong communication skills, and the ability to communicate complex data problems and solutions across the company

We hire only the best people. Here are the benefits to being top-notch: 

  • The opportunity to work with some of the best innovators in the industry
  • Generous healthcare coverage.
  • 401(K) with company match.
  • Paid Time Off
  • Paid parental leave
  • Tuition reimbursement
  • Annual wellness allowance
  • Profit Sharing