Manager - Data Science (Product Analytics)
US States: Arizona, California, Colorado, Connecticut, District of Columbia, Florida, Georgia, Idaho, Illinois, Indiana, Iowa, Maryland, Massachusetts, Michigan, Minnesota, Missouri, New Jersey, New Mexico, New York, North Carolina, Ohio, Oklahoma, Oregon, Pennsylvania, Puerto Rico, Rhode Island, Tennessee, Texas, Utah, Vermont, Virginia, Washington, West Virginia, Wisconsin and Wyoming Countries: Brazil, Canada, Colombia, France, Germany, Ghana, India, Indonesia, Italy, Kenya, Mexico, Morocco, Netherlands, Poland, Singapore, South Africa, Spain, Switzerland and the United Kingdom, UTC+1 to UTC-8, available for critical meetings and synchronous work between 14:00 and 22:00 UTCFull-TimeManager
Salary132439 - 192799 USD per year
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Job Details
- Required Skills
- HadoopSpark
Requirements
- Deep experience with experimental design and statistics applied to internet-scale audience or user experience data
- Experience collaborating with product development teams in a fast-paced environment
- Prior experience as a people manager
- Demonstrated commitment to equity, inclusion, and diversity
- Experience with large-scale data processing & storage tools
- Curiosity and critical thinking skills
- High emotional intelligence as a coach and mentor
- Strong collaboration skills and an empowerment approach to management
- Commitment to the mission and values of the organization
- Self-motivated with an ability to navigate through ambiguity and complexity
Responsibilities
- Lead the Product Analytics team to guide strategies and tactics
- Manage a team of data scientists to provide quantitative data and insights for product development
- Be accountable for the timely delivery, data accuracy, and consistent reporting of the team's work
- Support the design of data products and tools to make data accessible
- Ensure timely delivery of accurate quantitative data and insights, balancing speed with rigor
- Provide people management for a team of roughly seven data scientists
- Mentor team members on critical thinking, data-informed storytelling, technical skillset, and stakeholder partnership
- Partner with the Experiment Platform & Data Engineering teams to build and maintain data products
- Collaborate with product teams and colleagues in Research & Decision Science to foster data-informed decisions
- Continuously develop and improve experimentation and measurement best practices, product health metrics, visualizations, and reports
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