The Personalization and Loyalty team's mission is to make company the destination of choice for our customers. We drive loyalty by delivering what our customers want—at the right time, with the right value—creating meaningful connections that deepen their relationship with our company. As part of this organization, the team applies statistical science, causal inference, and AI to design experiments, measure impact, and scale insights that drive customer value and loyalty.
Open to relocation but must be within first 3 months of employment
Could consider Chicago if no local candidates can be found, but they would need to travel on occasion to Cincinnati
Open to remote, but must be a perfect fit
We're seeking a Data Scientist to help shape the future of our AI and science capabilities. This is a senior individual contributor role for a technically strong, forward-thinking data scientist who can advance our 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 our space.
Advance our 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.
Apply and extend causal ML and econometric methods (e.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.
3+ years of applied data science experience, with demonstrated progression in scope and technical complexity
Hands-on experience with Generative AI applications, including one or more of: LLM fine-tuning, prompt engineering, RAG pipelines, or agentic workflow development
Familiarity with causal ML and/or causal inference methods (e.Strong proficiency in Python, SQL, and Git
Experience with Azure and Databricks, or comparable cloud-based data science platforms
Experience contributing to production-quality ML systems using software engineering best practices
AI – Not a dealbreaker if they do not have a ton of experience, but must be willing to learn
Experience with MLOps practices including workflow orchestration, model monitoring, reproducibility, and deployment
Experience in retail, CPG, media, or marketplace analytics
Familiarity with experimentation frameworks and measurement pipelines
Open to relocation but must be within first 3 months of employment
Could consider Chicago if no local candidates can be found, but they would need to travel on occasion to Cincinnati
Open to remote, but must be a perfect fit
We're seeking a Data Scientist to help shape the future of our AI and science capabilities. This is a senior individual contributor role for a technically strong, forward-thinking data scientist who can advance our 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 our space.
Advance our 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.
Apply and extend causal ML and econometric methods (e.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.
3+ years of applied data science experience, with demonstrated progression in scope and technical complexity
Hands-on experience with Generative AI applications, including one or more of: LLM fine-tuning, prompt engineering, RAG pipelines, or agentic workflow development
Familiarity with causal ML and/or causal inference methods (e.Strong proficiency in Python, SQL, and Git
Experience with Azure and Databricks, or comparable cloud-based data science platforms
Experience contributing to production-quality ML systems using software engineering best practices
AI – Not a dealbreaker if they do not have a ton of experience, but must be willing to learn
Experience with MLOps practices including workflow orchestration, model monitoring, reproducibility, and deployment
Experience in retail, CPG, media, or marketplace analytics
Familiarity with experimentation frameworks and measurement pipelines
Data Scientist (Cincinnati) in cincinnati at Unknown Company
This position is listed as full time and able to be worked remotely.