Binance is hiring a

Web3 Manager, Product Data Science

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.

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