Top Senior Data Science Jobs in Cincinnati, OH

The Senior Data Scientist will analyze datasets, develop predictive models, and collaborate with stakeholders to enhance analytics apps and drive actionable insights.

The Senior Data Scientist will develop business analytics functions, manage data projects, conduct statistical analysis, and collaborate with stakeholders on predictive models and insights.

Lead the development of intelligent decision engines modeling customer intent in real-time using advanced data science techniques such as causal inference and machine learning. Collaborate with cross-functional teams to optimize systems for search, fulfillment, and customer experience.

The Staff Data Scientist will develop machine learning models, collaborate with cross-functional teams, and use analytics to drive business growth and improve credit risk assessment.

Develop and tune ML models, productionize and deploy strategies for ML systems, and align cross-functionally to communicate performance metrics.

As an AI-First Data Scientist, you will design and deploy ML solutions, conduct causal analysis, and automate intelligence in decision-making processes. You will work closely with senior operators and business leaders, translating complex problems into data-driven solutions while ensuring model performance and scalability.

The Senior Data Scientist will design, develop, and own machine learning systems for document verification focusing on computer vision and deep learning. Responsibilities include technical leadership, engaging with customers, and collaborating with engineering and product teams.

Lead development and deployment of machine learning and analytics products for mortgage lending. Design data pipelines, ensure data quality, build predictive models, communicate insights, mentor junior staff, and partner with engineering and DevOps for scalable MLOps solutions.

Lead development and operationalization of LLM, agentic, and image AI solutions for diagnostics. Build multimodal datasets, implement RAG and agent workflows, apply ML and statistical methods (DoE, Bayesian optimization, causal/survival/longitudinal), analyze RWE/RWD, and integrate insights across clinical, regulatory, and product teams to drive diagnostic and business impact.

Design, build, and deploy end-to-end production ML systems for audience targeting, lookalike generation, and propensity scoring. Own ML lifecycle from experimentation to production monitoring, leverage distributed/cloud platforms, implement vector similarity and embedding systems, engineer scalable features, and collaborate with engineering and product teams to ensure model quality and operational reliability.

The Geospatial Scientist leads data management initiatives, oversees data governance, and ensures quality and compliance of geospatial data for DHS.

Lead development and operationalization of LLM, agentic, and image AI solutions for diagnostics. Build multimodal datasets, develop production-grade models and RAG/agent pipelines, perform RWE analytics, and integrate insights across clinical, regulatory, R&D, and product teams to drive diagnostic performance and patient impact.

Lead development and operationalization of LLMs, agentic and image AI solutions; build multimodal datasets; develop production-grade models, RAG pipelines and agent workflows; run RWE analytics and Bayesian optimization for assay/R&D acceleration; deploy solutions on Azure/Snowflake/Databricks and integrate insights into clinical, regulatory, and product programs.

Lead analytics for claim decisioning by framing ambiguous problems, building scalable data models and pipelines, designing metrics, and deploying analytical and ML solutions. Partner cross-functionally to measure decision quality, operational performance, and payment accuracy, iterating quickly to deliver measurable impact.

Lead the design and implementation of AI-driven search algorithms and models. Collaborate with teams to optimize search performance and personalize user experiences. Mentor junior staff and stay updated on latest AI advancements.

The Senior Data Scientist at Bluesight will develop machine learning models, collaborate on analytics projects, communicate findings, and elevate the analytics team's skills.

As a Senior Data Scientist, you will lead data initiatives by setting goals, architecting data models, enhancing data quality, and mentoring team members to drive impactful business decisions at SmithRx.

As a Senior Data Scientist, you will evaluate revenue growth opportunities, develop analytical frameworks, create executive reports, and ensure data accuracy, influencing business decisions through strong technical execution and communication.

The Senior Data Scientist will evaluate revenue growth opportunities, develop analytical frameworks, produce reports, and ensure data accuracy for decision-making.

Lead custom analytics and ML model development for non-prime lending using traditional and alternative data. Scope and deliver credit strategies (underwriting, pricing, collections), engineer features, evaluate data sources, present insights to clients, and support model implementation, monitoring, and optimization.

As a Senior Data Scientist, you will develop statistical models and machine learning algorithms to improve patient enrollment and trial management while ensuring compliance in a healthcare data environment.

The role involves engineering consumer-level attributes, applying statistical techniques, building dashboards, and collaborating with various teams to enhance credit-related decisions based on data insights.

The role involves developing ML models for anomaly detection, time series forecasting, and predictive analytics for sewer infrastructure. Collaboration with engineering and data teams is essential to deliver insights effectively.

The Lead Data Scientist will build pricing systems, lead experiments, mentor teammates, and influence strategy across various departments based on data-driven insights.

The role involves building Marketing Mix Models, analyzing geo-based experiments, creating measurement infrastructure, and communicating insights to stakeholders.