Data Scientist

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.

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  Design and implement causal inference and causal machine learning solutions.

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  Measure the impact of business treatments on customer behavior, revenue, retention, and engagement.

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  Apply statistical methods including:

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    Difference-in-Differences

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    Matching

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    Panel Data Models

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    CATE Estimation

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    Uplift Modeling

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    Heterogeneous Treatment Effect Modeling

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  Define treatments, control groups, counterfactuals, outcome metrics, and evaluation windows.

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  Build scalable, production-ready ML pipelines using software engineering and MLOps best practices.

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  Partner with business and product teams to convert business problems into scientific solutions.

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  Develop and integrate Generative AI solutions including RAG, prompt engineering, LLM workflows, fine-tuning, and agentic AI where applicable.

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  Evaluate emerging AI/ML technologies for production adoption.

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  Present technical findings and business impact to both technical and non-technical stakeholders.

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  Provide technical guidance and code reviews to team members.

• 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.

• 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.