Sr. Data Scientist (Causal Inference & Experimentation)

Duration: 12+ Months (Contract-to-Hire)Location: Cincinnati, OH (Onsite 5 Days/Week)Candidates willing to relocate within the first 2 months will be considered.

Job Summary: o Seeking a Senior Data Scientist to develop and scale AI and advanced analytics solutions focused on experimentation, causal inference, and customer insights. The ideal candidate will have expertise in statistical modeling, econometrics, Generative AI, and production machine learning while partnering with cross-functional teams to deliver business-impacting solutions.

Required Skills: o 3+ years of hands-on Data Science experience. o Strong experience with Causal Inference, Causal ML, and Econometrics. o Experience designing and analyzing A/B tests, experimentation, and treatment effect measurement. o Hands-on experience with Generative AI, including LLMs, Prompt Engineering, RAG, or Agentic AI. o Strong programming skills in Python, SQL, and Git. o Experience with Azure, Databricks, or similar cloud-based ML platforms. o Experience building and deploying production ML solutions using software engineering best practices o Strong communication skills with the ability to translate technical findings into business value o Bachelor''s or Master''s degree in Data Science, Statistics, Computer Science, Economics, Applied Mathematics, or a related quantitative field

Preferred Skills: o MLOps (CI/CD, model deployment, monitoring). o Retail, CPG, eCommerce, or customer analytics experience. o Personalization, recommendation systems, or loyalty analytics. o Experience mentoring or leading technical initiatives.

Key Responsibilities: o Design, develop, and deploy AI and Generative AI solutions using LLMs, RAG, and agentic workflows. o Apply causal inference and econometric methods to measure business impact and customer behavior. o Build scalable ML models and experimentation frameworks for production environments. o Partner with product managers and business stakeholders to define analytics strategy and prioritize initiatives. o Research and implement emerging AI/ML technologies to improve business outcomes. o Communicate complex analytical insights to both technical and non-technical audiences.