Senior Data Scientist FinTech - Toronto, ON, Canada - Robinhood

Description

Insights from data power many decisions at Robinhood. Our company trajectory is shaped by the systems, tools, and analytics driven by this exceptional data science team.

As a senior product data scientist, you will play a critical role in optimizing and enhancing the product's performance by harnessing data and analytics to drive informed decision-making and innovations.

As a member of this cross-functional group, you will collaborate closely with partners in product, engineering, user research, design, marketing, finance and compliance to unlock the potential of our data and shape the future of the brokerage products.

The role is located in the office location(s) listed on this job description which will align with our in-office working environment.

Please connect with your recruiter for more information regarding our in-office philosophy and expectations.

Initiate and execute large analysis projects to deepen understanding of customers, uncover product improvement opportunities, provide actionable recommendations, and drive impact for our business.

Develop and maintain machine learning models and statistical models to enhance the product's performance and user experience.
Develop experiment design and experiment analysis frameworks.
Define metrics system to measure product performance. Build dashboards and reports to understand and monitor these metrics.

Create data visualizations and reports, synthesize data insights to compelling stories, to effectively communicate them to cross-function partners, stakeholders, and senior executives.

Design, develop and maintain data pipelines with outstanding craftsmanship.
Mentor others as needed to uplift the team's capacity, and to democratize data knowledge and data insights within the company
Graduate degree in a quantitative field such as mathematics, economics, statistics, engineering, computer science, etc.
~5+ years of demonstrated experience working in product analytics or data science
~ Track record of initiating, and executing large / complex deep dive projects
~ Track record of developing data insights that generates business impact
~ Solid understanding of statistics. Practical experience in AB testing and causal inferenc
~ Solid understanding of ML algorithms. Practical experience in applying ML to uncover valuable insights, to improve user experience and product performance
~ Expert level SQL, Python skills
~ Excellent data visualization skills and data storytelling skills
~ Experience in product data science in a dynamic, innovative, and fast-paced high tech environment