Senior Manager, Growth Algorithms
New
S
Stitch FixPersonalized retail
Remote USAFull-TimeManager
Salary$200,000 — $245,000 USD
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Job Details
- Experience
- 5+ years of experience applying machine learning, experimentation, and causal inference to business problems; 2+ years of experience as a technical team lead or direct people manager
- Required Skills
- PythonMachine LearningPeople ManagementGenerative AI
Requirements
- Hold a bachelor’s degree in a quantitative field such as Computer Science, Statistics, Economics, Physics, Mathematics, or Operations Research; a master’s degree or PhD is preferred.
- Have 5+ years of experience applying machine learning, experimentation, and causal inference to business problems.
- Have 2+ years of experience as a technical team lead or direct people manager.
- Demonstrate experience developing talent and delivering outcomes through others.
- Bring practical expertise in experiment design and interpretation, including metric design, statistical power, sources of bias, and decision-making under uncertainty.
- Have cross-functional leadership experience defining analytics ownership, decision rights, and best practices across Data Science, Product, Engineering, Marketing, and Analytics teams.
- Show a track record of creating data science strategy, translating it into a focused portfolio, and connecting team work to client and business outcomes.
- Demonstrate ability to challenge assumptions, simplify complex systems or processes, and stop or consolidate lower-value work while leading change transparently and empathetically.
- Bring technical fluency across analysis, experimentation, machine learning, system design, and production-quality Python code.
- Be able to explain evidence, uncertainty, tradeoffs, and recommendations to executives, business partners, and technical audiences.
- Use sound judgment to assess the value of traditional machine learning, generative AI, AI-assisted development, and ad hoc analytical approaches.
Responsibilities
- Set and communicate a clear data science vision for Growth Algorithms and turn growth goals into a focused portfolio.
- Partner with Product, Marketing, Engineering, Finance, Design, and Enterprise Analytics on ownership and best practices for experimentation, product analytics, AI/ML measurement, and decision support.
- Improve experimental design and interpretation by incorporating statistical evidence and business context into recommendations.
- Guide strategy for Next Best Action, lifecycle personalization, predictive value, CRM and paid media, the onboarding funnel, and incentives.
- Challenge established approaches and create new technical, analytical, product, or operating methods when needed.
- Consolidate overlapping capabilities, retire low-value work, reduce legacy complexity, and focus team capacity on high-impact opportunities.
- Lead full-stack data scientists through opportunity sizing, experiment or model design, production deployment, measurement, monitoring, on-call, and incident response.
- Partner with Engineering on reliable systems and choose the simplest effective approach.
- Build an inclusive, high-performing team grounded in ownership, candid feedback, curiosity, kindness, and continuous learning.
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