Senior Data Scientist II

Design, build, and deploy predictive and causal models that power personalization, retention, and monetization strategies.

Apply advanced statistical methods, including Bayesian inference, causal impact analysis, and hierarchical modeling, to guide decision-making.

Develop and operationalize experimentation and measurement frameworks that ensure accurate attribution and reproducibility across Fetch’s products.

Quantify the impact of key business and product initiatives, translating complex model outputs into actionable insights.

Design and analyze experiments that test hypotheses about user behavior, product features, and marketing initiatives.

Establish metrics and analytical frameworks that measure Fetch’s progress toward strategic growth and retention goals.

Partner closely with Product, Engineering, and Data Product teams to transform insights into scalable data products and intelligent systems.

Communicate complex analyses through clear narratives and visualizations that drive executive understanding and action.

Mentor and collaborate with peers to strengthen Fetch’s scientific rigor, data culture, and analytical storytelling capabilities.

Leverage tools and technologies such as Python, SQL, Snowflake, dbt, Airflow, Spark, and AWS to build and scale robust data science solutions.

Champion best practices in experimentation, model validation, reproducibility, and governance.

Advance Fetch’s use of AI/ML tools for automation, documentation, and anomaly detection, emphasizing validation and responsible use.

8+ years of experience in data science, machine learning, or applied analytics with proven impact in product-driven environments.

Deep expertise in statistical modeling, experimental design, and causal inference.

Strong proficiency in SQL and at least one programming language (Python preferred).

Experience working with large-scale data systems such as Snowflake, dbt, Airflow, or Spark.

Proven ability to communicate complex technical insights to non-technical stakeholders and drive strategic decision-making.

Bachelor’s degree in Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field.

Advanced degree (Master’s or Ph.D.) in a quantitative discipline.

Experience deploying ML models into production and managing model lifecycle and performance.

Background in consumer technology, ad tech, or personalization systems.

Experience building frameworks that improve experimentation velocity and decision quality.

Familiarity with privacy-preserving data modeling and compliance standards such as GDPR or CCPA.

Mentorship experience or demonstrated leadership in scientific or analytical development.

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)