2 дня назад
Staff Data Scientist, Product (Product Analytics)
115 000 - 230 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Staff Data Scientist, Product (Product Analytics): Building quantitative frameworks, experiments, causal analyses, and decision models that shape product, engineering, and investment decisions with an accent on experimentation, metric design, and behavioral insight. Focus on designing quasi-experiments, applying advanced causal inference methods, modeling pricing and retention trade-offs, and translating complex findings for senior leadership.
Location: Bethesda, Maryland, United States
Annual salary: $115,000–$230,000
Company
is a large U.S. auto insurer and a member of the Berkshire Hathaway family of companies.
What you will do
- Partner with product, engineering, and design leaders to frame business questions and influence roadmap decisions.
- Define product goals, guardrails, metric trees, and measurable drivers of outcomes.
- Design, power, and analyze A/B and quasi-experiments, including treatment heterogeneity and long-term effects.
- Apply causal inference methods such as difference-in-differences, synthetic control, instrumental variables, propensity scoring, and switchback designs.
- Build opportunity-sizing, forecasting, and ROI models for pricing, growth, retention, and investment decisions.
- Lead investigations into user behavior, funnels, retention, and engagement; communicate recommendations to senior leadership and mentor junior analysts.
Requirements
- 8+ years of experience in product analytics, decision science, data science, or a related quantitative role at a technology company.
- Strong experience with well-powered A/B testing, statistical analysis, bias and variance diagnosis, interference, and non-stationarity.
- Applied statistics and causal inference experience, with the ability to select appropriate methods for specific questions.
- Advanced SQL and working proficiency in Python or R for analysis, modeling, and reproducible workflows.
- Ability to define product metric frameworks, influence product decisions, and communicate clearly with executives.
- Bachelor’s degree or higher in statistics, economics, computer science, mathematics, operations research, or a related quantitative field, or equivalent practical experience.
Nice to have
- Experience with Bayesian methods, hierarchical models, sequential testing, or uplift modeling.
- Background in growth, pricing, monetization, marketplaces, recommendations, insurance, or financial services.
- Experience partnering with machine learning engineers on production models, offline evaluation, online metrics, and guardrails.
- Contributions to experimentation platforms, metric stores, or measurement tooling.
- Master’s degree or PhD in a quantitative discipline.
Culture & Benefits
- Personalized development programs, mentorship, and certification assistance.
- Inclusive and collaborative culture focused on shared success.
- Competitive pay, benefits, and flexibility supporting employee well-being.
- will consider sponsoring a qualified new applicant for employment authorization.
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