Senior Data Scientist, Media
THE ROLE
The Marketing Analytics team at Peloton is a full-stack team responsible for data, analytics, and predictive modeling to accelerate and optimize connected fitness membership growth across all marketing channels. The team consists of 3 functional areas: Analytics Engineering, Marketing Science, and Product Marketing Analytics.
Peloton is looking for a talented individual to join the Channel Optimization team within the broader Marketing Science function. This person will partner closely with the media team to measure and optimize Peloton’s marketing investment to grow Connected Fitness sales efficiently and effectively.
RESPONSIBILITIES
- Partner with the Acquisition Marketing team to measure and optimize media performance on digital and offline channels.
- Provide thought leadership in experimental design and statistical analysis to measure incremental lift and marginal returns. You will design and evangelize marketing experiments such as A/B testing, multivariate testing, geo matched market, pre/post analysis, causal inference, and more.
- Refine understanding of media’s impact through channel measurement tools such as multi-touch attribution, incrementality lift studies, and platform and partner tools (Facebook Advanced Analytics & Google Data Hub).
- Define business KPIs and build data visualization, advanced reports, and dashboards to track media performance. Communicate results to cross-functional stakeholders: product marketing, media, brand marketing, executives, and agencies.
- Update and maintain internal TV spike attribution model to measure the impact of TV advertising across products and markets.
- Perform ad hoc analysis and deep dive investigations to generate actionable insights.
- Collaborate with Analytics Engineers to maintain and update ETL jobs, data models, and advanced analytical models.
QUALIFICATIONS
- BA/BS degree, preferably in a technical field.
- 4-6 years of professional experience in marketing analytics or data science field.
- Strong understanding of multi-touch attribution modeling, marketing mix modeling, and incrementality lift measurement.
- Practical experience in applied statistics and data science methodologies (e.g. data modeling and predictive analytics, multivariate regression analysis, machine learning).
- Strong experience with SQL and working with large sets of data.
- Strong experience with Python/R for data wrangling, modeling, and analyses.
- Experience with data visualization products such as Looker or Tableau.
- Comfortable with spreadsheet and presentation tools (Excel, Powerpoint).
- Strong presentation skills and ability to effectively communicate complicated analyses to non-technical team members.
- Can do attitude, ability to quickly pivot between projects and priorities and thrive in a fast paced environment.
ABOUT PELOTON:
Peloton uses technology + design to connect the world through fitness, empowering people to be the best version of themselves anywhere, anytime. We have reinvented the fitness industry by developing a first-of-its-kind subscription platform. Seamlessly combining hardware, software, and streaming technology, we create digital fitness and wellness content and products that Members love. In 2020 Peloton committed to becoming an antiracist organization with the launch of the Peloton Pledge. Learn more, here.
“Together We Go Far” means that we are greater than the sum of our parts, stronger collectively when each one of us is at our best. In order to be the best version of Peloton, we are deeply committed to building a diverse workforce and inclusive culture where all of our team members can be the best version of themselves. This work has no endpoint; it is the constant work of running an organization that strives to reach its full potential. As a first step in our commitment, we announced the Peloton Pledge to invest $100 million over the next four years to fight racial injustice and inequity in our world, and to promote health and wellbeing for all, from the inside out.
Peloton is an equal opportunity employer and committed to creating an inclusive environment for all of our applicants. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. If you would like to request any accommodations from application through to interview, please email: [email protected]
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