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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # GenAI Data Scientist - **Company:** Eliassen Group - **Location:** Blue Ash, OH, United States - **Experience:** Experienced - **Salary:** $124,800.0 - $145,600.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Microsoft Azure, Cloud Database, Continuous Integration, Monitoring of Systems, Python (Programming Language), Machine Learning, Performance Tuning, Software Engineering, SQL Databases, Workflow Management Systems, Large Language Models, Prompt Engineering, Generative AI, Git, Machine Learning Operations, Software Version Control, Databricks - **Published:** September 20, 2026 - **Apply:** https://dejobs.org/x/x/69DCD73D8C3243FD8DE24F1AE8C71155/job/ ## About the Role * 3+ years of applied data science experience with progression in scope and technical complexity. * Hands-on experience with Generative AI applications such as LLM fine-tuning, prompt engineering, RAG pipelines, or agentic workflow development. * Familiarity with causal ML and causal inference methods including CATE, heterogeneous treatment effect modeling, DiD, and matching. * Proficiency in Python, SQL, and Git. * Experience with Azure and Databricks or comparable cloud-based data science platforms. * Contributions to production-quality ML systems using software engineering best practices. * Ability to partner with product managers and stakeholders to translate business needs into science solutions and roadmap priorities. * Strong oral and written communication skills to translate between technical and business audiences. * Comfort with ambiguity and ability to operate effectively in evolving problem spaces and contribute to early-stage vision and strategy. * Preferred: Experience with MLOps practices including workflow orchestration, model monitoring, reproducibility, and deployment. * Preferred: Experience in retail, CPG, media, or marketplace analytics. * Preferred: Ability to informally mentor or coach peers in technical best practices. * Preferred: Familiarity with experimentation frameworks and measurement pipelines. Recruitment Transparency Notice ## Description Our client seeks a Data Scientist to advance Gen AI and causal ML capabilities, lead end-to-end development of scalable science solutions, and partner with product and cross-functional teams to drive vision and strategy in personalization and loyalty. The role focuses on statistical science, causal inference, AI-driven experimentation, and the integration of insights that deliver customer value and loyalty., * Advance AI capabilities by designing, developing, and deploying Gen AI solutions including LLM fine-tuning, prompt engineering, RAG pipelines, agentic workflows, and integration of Gen AI into existing measurement and science workflows. * Lead end-to-end development and scaling of data science solutions from research and experimentation through productionization, ensuring solutions are robust, reproducible, and maintainable. * Partner with product managers and cross-functional stakeholders to shape the vision, roadmap, and prioritization of science products and capabilities in personalization and loyalty. * Contribute to the vision and early development of a holistic science layer to connect and consolidate scattered science capabilities into a unified, scalable framework. * Apply and extend causal ML and econometric methods such as CATE, DiD, matching, and panel methods to support measurement, experimentation, and personalization at scale. * Build, maintain, and improve production ML and experimentation pipelines using sound MLOps and software engineering practices including CI/CD, version control, testing, and documentation. * Research and evaluate emerging AI/ML technologies and methodologies, identifying opportunities to bring state-of-the-art approaches into production. * Serve as a technical leader and subject matter expert, providing guidance and informal mentorship to peers and evolving into a formal mentor as junior talent joins the team. * Communicate complex technical findings and methodologies clearly to both technical and non-technical audiences, including leadership and product stakeholders. ## Related Videos - [Inside the AI Revolution: How Microsoft is Empowering the World to Achieve More](https://www.wearedevelopers.com/videos/869-inside-the-ai-revolution-how-microsoft-is-empowering-the-world-to-achieve-more) - [Your imaginations is (no longer) the limit: how Generative AI empowers people to be creative](https://www.wearedevelopers.com/videos/741-your-imaginations-is-no-longer-the-limit-how-generative-ai-empowers-people-to-be-creative) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [How E.On productionizes its AI model & Implementation of Secure Generative AI.](https://www.wearedevelopers.com/videos/623-how-e-on-productionizes-its-ai-model-implementation-of-secure-generative-ai) - [The shadows that follow the AI generative models](https://www.wearedevelopers.com/videos/624-the-shadows-that-follow-the-ai-generative-models) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Got AI ideas but no money? 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