As a Data Science Manager at Reddit, you will collaborate closely with cross-functional partners to help us build and improve the systems that continuously drive our user growth. You will be responsible for driving the adoption of strategic and tactical recommendations based on deep experience with Reddit products and data skills.

Key responsibilities include:

• Serving as a thought-partner for product managers, engineering managers, and leadership to communicate and shape the roadmap and strategy for Reddit.
• Being proactively involved in all phases of product development, including ideation, exploratory analysis, opportunity sizing, metrics design, offline modeling, experimentation, and decision-making.
• Having a keen interest in the collection and quality of underlying data, including experiment design and analysis, data deep dive, ETLs, reporting dashboards, and data aggregations needed for business tracking and/or ML model development.

Requirements include:

• An advanced degree in a quantitative field such as statistics, mathematics, physics, economics, or operations research.
• 10+ years of industry experience for masters holders, or 6+ years for PhD holders.
• Experience in driving product strategy and roadmaps through analytics, ideally for consumer technology products and marketplaces.
• Leadership experience as a people manager, leading a team of 5+ data scientists.
• Expertise in causal inference, A/B testing experimentation, metric definition and governance, and product strategy.
• Proficiency in SQL and Python/R for hands-on analysis.

Benefits include comprehensive healthcare benefits, income replacement programs, 401k with employer match, global benefit programs, family planning support, gender-affirming care, mental health and coaching benefits, flexible vacation and paid volunteer time off, and generous paid parental leave.

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The MaaS Data Science team is central to all money movements, embedded finance, and platform solutions for our biggest and most complex customers. The two roles available are in Embedded Finance (Capital, Issuing) and Connect (Stripe's solution and growth suite for platforms and marketplaces).

The Growth Data Science team helps businesses on Stripe get started both quickly and effectively. We work closely with Growth product and engineering leads to optimize every step of the user journey, from awareness and acquisition, through product adoption, to usage growth and retention.

Responsibilities:

• Drive the roadmap and priorities for your team, and work with many Stripe leaders across the company to enhance our ability to be data driven.
• Collaborate with stakeholders across the organization such as engineering, analytics, operations, finance, and marketing.
• Lead and manage processes to help the team do its best work and engage effectively with the rest of Stripe.
• Manage a high-performing team of data scientists, supporting them to achieve a high level of technical excellence and advance in their careers.
• Recruit and onboard great data scientists, in collaboration with Stripe’s recruiting team.
• Contribute to broad data science initiatives as a member of Stripe’s data science management team.

Requirements:

• PhD or MS or BS in a quantitative field (e.g., Statistics, Operations Research, Economics, Computer Science, Engineering).
• At least 3 years of direct management experience leading data science or ML teams, and 10 years of overall data science experience.
• Demonstrated expertise in designing metrics and guiding business decisions with data.
• Technical expertise to drive clarity with staff and senior scientists about architecture and strategic modeling decisions.
• Managed teams that have built and shipped machine learning systems and data products at scale, and have hands-on experience with challenging problems.
• Work very well cross-functionally, and are able to think rigorously and make hard decisions and tradeoffs.
• Clear and persuasive communication skills in writing and verbally.
• Thrive on a high level of autonomy and responsibility.
• Foster a healthy, inclusive, challenging, and supportive work environment.

Preferred Requirements:

• Comfortable working with geographically distributed teams.
• Expertise in time series forecasting, predictive modeling, or optimization.
• Expertise in data design and building scalable data architectures.

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