Data Scientist

Job Summary

We are seeking an experienced Data Scientist to drive causal inference, experimentation, measurement, personalization, and applied AI initiatives. The ideal candidate will have hands-on experience applying causal inference and econometric techniques to measure business impact, build production-ready machine learning solutions, and translate analytical insights into measurable business outcomes. Experience with Generative AI is a plus but not the primary requirement.

Key Responsibilities

• Design and implement causal inference and causal machine learning solutions.
• Measure the impact of business treatments on customer behavior, revenue, retention, and engagement.
• Apply statistical methods including:
• Difference-in-Differences
• Matching
• Panel Data Models
• CATE Estimation
• Uplift Modeling
• Heterogeneous Treatment Effect Modeling
• Define treatments, control groups, counterfactuals, outcome metrics, and evaluation windows.
• Build scalable, production-ready ML pipelines using software engineering and MLOps best practices.
• Partner with business and product teams to convert business problems into scientific solutions.
• Develop and integrate Generative AI solutions including RAG, prompt engineering, LLM workflows, fine-tuning, and agentic AI where applicable.
• Evaluate emerging AI/ML technologies for production adoption.
• Present technical findings and business impact to both technical and non-technical stakeholders.
• Provide technical guidance and code reviews to team members.