Launched in 2019, Binance.US is the fastest growing and most integrated digital asset marketplace in the United States, powered by matching engine and wallet technologies license from the world’s largest cryptocurrency exchange - Binance. Our mission is to provide liquidity, transparency, and efficiency to financial markets by creating products that leverage crypto to unlock the power of everything. We build bridges between traditional finance and digital markets that enable growth for all—empowering the future of finance. Binance.US is operated by BAM Trading Services.
Binance.US, one of the most recognized brands in cryptocurrency, is looking for a Product Data Science Leader to join our growing Data organization. You will be embedded as a leader in the Product organization, working with and supporting the different product teams on a day-to-day basis. The ideal candidate is a strategic self-starter with a solid foundation in data science and proven track-record in product data science. You are not only strong in execution and delivery, but also extremely skilled in designing strategy, planning and building a team.
#LI-Hybrid
What You'll Do
- Build and execute an effective strategy and roadmap for the Product Data Team
- Develop and foster a rigorous data-driven culture within Product Data Science 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 monetisation 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
What You'll Need
- 10+ years prior experience in Product Data Science/Analytics
- 5+ years of experience at a tech company
- 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 needs
- Knowledge 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
Binance.US is an Equal Opportunity Employer. Our mission is to give Americans access to a broad array of digital assets, and we thrive because of the diverse and inclusive team that we are building. We do not discriminate against qualified employees or applicants because of race, color, religion, gender identity, sex, sexual preference, sexual identity, pregnancy, national origin, ancestry, citizenship, age, marital status physical disability, mental disability, medical condition, military status, or any other characteristic protected by local law or ordinance.
Binance.US complies with Federal Transparency in Coverage regulations by providing this link to machine readable files related to the health plans offered to our employees. The machine-readable files are formatted to allow researchers, regulators, and application developers to more easily access and analyze data including negotiated service rates, and out-of-network allowed amounts between health plans and healthcare providers.