As our Manager, Product Data Science, you will be embedded into the Product organization, working with and supporting the different product teams on a day-to-day basis. The ideal candidate is a self-starter with a solid foundation in data science and experience in product data analytics. You are not only strong in execution and delivery, but also comfortable managing strategy, planning and a team.
Responsibilities:
Build and execute an effective strategy and roadmap for the Product Data Team
Develop and foster a rigorous data-driven culture within Product Analytics and across the broader Product community by being the Data Leader in the Product team
Conduct and oversee research and deep dive data analysis to prioritize production efforts and growth opportunities; leverage insights to develop data-driven business cases to inform and influence product strategy & roadmap to maximize the product KPIs
Define, measure and consistently track health, technical, growth and monetization metrics for the product
Define and ensure the implementation of all the necessary tracking and AB testing for all the features and aspects of the product
Collaborate with other teams like marketing and risk to ensure growth and success of the product
Provide technical leadership to the rest of the Product Analytics team and drive execution to measure the effect of marketing efforts
Design and build tools for the Product team that help in automating processes and facilitating smart decision making
Conceptualize and prototype machine learning models to improve engagement and monetization KPIs
Recruit, manage, and mentor a team of motivated Product data scientists/analysts.
Requirements:
5+ years prior experience in Product and 5+ years in Data Science/Analytics
5+ years of experience at a tech company
2+ years of people management experience
Fluency with SQL and expertise with R or Python
Experience with designing and developing compelling data visualizations and dashboards
Excellent product sense from growth point of view and deep knowledge of the product data science/analytics needsKnowledge in applied statistics (e.g. hypothesis testing, regressions, predictive modeling) and experimentation (e.g. A/B testing) in a tech product setting
Excellent communication and presentation skills
Ability to translate complex data into actionable insights for a non-technical audience
Proactive and autonomous
Experience with Machine Learning Analytics/Prototyping is a plus
Good understanding of statistics is a plus
Experience in recruiting data scientists/analysts is a plus.