Data Scientist

ABOUT THE ROLE

As a data scientist, you’ll be responsible for understanding our business through data, uncovering the latest interesting insights, and applying them to the business in ways that achieve transformative impact. You’ll be the voice of data for the Supply Chain and Global Member Support organizations informing their understanding of what drives member satisfaction and operational efficiency with a focus on measurable results. As part of the Data Science team you’ll work with data scientists, analysts, and engineers that interface with the entire company, cross-pollinating analytic and business insights to the benefit of all Peloton members and employees.

YOUR DAILY IMPACT AT PELOTON

• Influence and advise the business on how to optimize operations using data and insights
• Perform deep dive analysis to answer core business questions
• Collaborate with cross-functional partners on measurement strategy, data collection
• Define the data capabilities required for ongoing reporting across the organization
• Build and maintain data driven optimization models, experiments, forecasting algorithms, and machine learning models
• Create dashboards and alerting to align teams around the core business performance metrics for Supply Chain and Global Member Support.
• Communicate recommendations clearly and concisely, seek buy-in from stakeholders, and drive decision making

YOU BRING TO PELOTON

• Master’s degree in Stats, Econ, Bus Admin, Data Sci, Data Analytics, or a rel field (or Bachelor’s degree with 5+ years experience)
• Minimum of 3-5 years proven business experience and technical expertise in data science
• Experience with Machine Learning, Statistics, or other data analysis tools and techniques
• Experience performing data extraction, cleaning, analysis and presentation for medium to large datasets
• Experience analyzing data with SQL, Python and/or R
• Experience with scientific computing and analysis packages such as NumPy, SciPy, Pandas, Scikit-learn, dplyr, or ggplot2
• Experience with statistics methods such as forecasting, time series, hypothesis testing, classification, clustering or regression analysis
• Proactive and self-motivated, and can work autonomously with strong organizational and time management skills
• Start-up experience a plus
• Understanding of analytic and optimization best practices around logistics, manufacturing, and customer service operations

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