Note: The job is a remote job and is open to candidates in USA. Fetch is an AI and data-driven company whose integrated AI and data organization supports business understanding, decision-making, and intelligent products. The Senior Data Scientist will own complex analyses and measurement frameworks for a product or business area, define KPIs, conduct experimentation and statistical modeling, and provide recommendations that improve user and business outcomes. The role partners with Product, Engineering, Marketing, and Data Product teams while mentoring junior practitioners and strengthening analytical rigor.
Responsibilities
- Independently design and execute complex analyses, statistical models, and measurement frameworks that inform product and business decisions
- Apply statistical methods such as experimental design, causal inference, predictive modeling, and Bayesian approaches based on the needs of the problem
- Translate ambiguous business questions into structured analytical approaches, identifying the appropriate metrics, methodologies, and data required
- Make thoughtful trade-offs between rigor, speed, precision, and practicality based on the business decision at hand
- Act as the primary analytical owner for a product or business area, defining and maintaining its core KPIs and measurement frameworks
- Proactively identify opportunities where analytics and experimentation can improve user behavior, revenue, conversion, retention, cost efficiency, or other key outcomes
- Design and analyze experiments, partnering with Product and Engineering to influence experimentation strategy and decision-making
- Connect metric movements and analytical findings to underlying business drivers, clearly articulating implications and recommended actions
- Quantify the impact of product and business initiatives and use those insights to influence roadmap and prioritization decisions
- Partner closely with Product, Engineering, Marketing, and Data Product stakeholders to inform team-level product and business decisions
- Communicate complex analyses through clear narratives and visualizations, including assumptions, trade-offs, confidence levels, and expected business impact
- Translate technical and analytical concepts for non-technical partners and navigate cross-functional dependencies effectively
- Increase data literacy by making metrics, analyses, and recommendations accessible and actionable for stakeholders
- Informally mentor junior data scientists and analysts, helping strengthen their technical judgment and analytical approaches
- Leverage tools and technologies such as Python, SQL, Snowflake, dbt, Airflow, Spark, and AWS to conduct and scale analytical work
- Apply strong practices in experimentation, model validation, reproducibility, and governance
- Use AI/ML tools thoughtfully to improve analytical workflows, automation, documentation, and anomaly detection while maintaining appropriate validation
Skills
- * 5+ years of experience in data science, machine learning, or applied analytics, with demonstrated ownership of complex analytical problems in product-driven environments
- * Strong expertise in statistical modeling, experimental design, and causal inference
- * Experience owning KPIs, measurement, or analytics for a product or business area and translating findings into actionable recommendations
- * Demonstrated ability to structure ambiguous business problems and connect analytical findings to business drivers such as revenue, cost, conversion, retention, or user behavior
- * Strong proficiency in SQL and at least one programming language, preferably Python
- * Experience working with large-scale data systems such as Snowflake, dbt, Airflow, or Spark
- * Proven ability to communicate complex technical insights, trade-offs, and confidence levels to technical and non-technical stakeholders
- * Ability to work independently while navigating cross-functional dependencies and escalating broader trade-offs appropriately
- * Bachelor's degree in Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field
- * Advanced degree in a quantitative discipline
- * Experience deploying or operationalizing predictive or statistical models
- * Background in consumer products, with experience using data to understand user behavior and inform engagement, retention, monetization, or other key customer outcomes
- * Experience building frameworks that improve experimentation velocity and decision quality
- * Familiarity with privacy-preserving data modeling and compliance standards such as GDPR or CCPA
- * Experience mentoring junior data scientists, analysts, or interns
Benefits
- Equity: We offer full-time employees equity in Fetch, so that everyone can benefit from Fetch’s growth.
- 401k Match: Dollar-for-dollar match up to 4%.
- Benefits for humans and pets: We offer comprehensive medical, dental and vision plans for everyone including your pets.
- Continuing Education: Fetch provides ten thousand per year in education reimbursement.
- Employee Resource Groups: Take part in employee-led groups that are centered around fostering a diverse and inclusive workplace through events, dialogue and advocacy. The ERGs participate in our Inclusion Council with members of executive leadership.
- Paid Time Off: On top of our flexible PTO, Fetch observes 9 paid holidays, as well as our year-end week-long break.
- Robust Leave Policies: 20 weeks of paid parental leave for primary caregivers, 14 weeks for secondary caregivers, and a flexible return to work schedule.
- Calvin Care Cash: Employees who are welcoming new family members will also receive a one time $2,000 incentive to assist employees with covering the cost of childcare, clothing, diapers and much more!
- Flexible Work Environment: Collaborate with your team in one of our stunning offices, or you can work fully remotely from anywhere in the US. We’ll ensure you are equally equipped with the hardware and software you need to get your job done in the comfort of your home. (applicable for most roles)
Company Overview
Company H1B Sponsorship