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.

Required Qualifications

• 3+ years of applied Data Science experience.
• Strong experience with causal inference, causal ML, econometrics, or experimentation.
• Experience measuring treatment effects and incremental business impact.
• Hands-on experience with:
• Difference-in-Differences
• Matching
• CATE
• Panel Data Analysis
• Uplift Modeling
• Heterogeneous Treatment Effects
• Strong Python and SQL programming skills.
• Experience with Git.
• Experience developing production-quality ML or analytics solutions.
• Strong analytical, communication, and problem-solving skills.
• Bachelor's or Master's degree in Statistics, Economics, Data Science, Computer Science, Applied Mathematics, or related quantitative field.

Preferred Qualifications

• Experience with Generative AI, RAG, Prompt Engineering, Fine-tuning, LLM Evaluation, or Agentic AI.
• Experience with Azure, Databricks, or similar cloud platforms.
• Experience with MLOps, deployment, orchestration, monitoring, and model lifecycle management.
• Experience building experimentation platforms or measurement pipelines.
• Retail, CPG, media, personalization, loyalty, or customer analytics experience.
• Experience mentoring technical teams.