Senior Data Scientist — Causal Inference for Growth & Pricing

Carbon Data Solutions; United States; Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Hybrid work model

Mentorship programs

Diversity & inclusion initiatives

Job summary

Back Market is seeking a marketplace economics expert to apply causal inference and advanced analytics to strategic questions about growth, pricing and supply on a global scale.

You will influence decisions across Supply and Pricing teams by designing experiments, building models, and translating results into actionable recommendations. The role emphasizes collaboration with Engineering and Business partners in a fast-paced, impact-driven environment.

Qualifications

• 4–8+ years applying causal inference and statistical methods to business problems.
• Advanced SQL and Python (and/or R).
• Experience driving strategic decisions through cross-functional collaboration.

Responsibilities

• Build causal inference models to understand the drivers of supply, pricing and assess the impact of marketplace policies and pricing initiatives.
• Design and analyse experiments and quasi-experiments, including holdout groups and treatment effects.
• Translate analytical findings into actionable recommendations, decision tools and guardrails for Revenue, Pricing and Supply teams.
• Lead cross-functional projects with Supply, Pricing, Business and Engineering teams.
• Establish best practices for causal inference, experimentation and impact measurement, and mentor other analysts.
• Communicate complex analytical work clearly to senior stakeholders and influence commercial decisions.

Skills

Causal inference

SQL

Python

R

Tools

dbt

Tableau

Job description

Back Market is seeking a marketplace economics expert to apply causal inference and advanced analytics to strategic questions about growth, pricing and supply on a global scale.

You will influence decisions across Supply and Pricing teams by designing experiments, building models, and translating results into actionable recommendations. The role emphasizes collaboration with Engineering and Business partners in a fast-paced, impact-driven environment.