Top Remote Data Science Jobs in Cincinnati, OH

Lead product analytics to inform strategy and optimize user experience: translate business questions into analysis, build reliable analytics infrastructure, run A/B tests and ML/statistical analyses, track funnels and cohorts, support 0-to-1 product launches, and communicate actionable insights to cross-functional teams.

Work with clients and engineers to audit marketing datasets, build analytics pipelines, and apply predictive models (segmentation, attribution, propensity) using SQL, Python, cloud big-data tools, and ML frameworks. Support implementations, develop analytic applications, and communicate findings to drive marketing outcomes.

Design and train LLMs and agentic systems for cybersecurity using RLHF/RLAIF and supervised fine-tuning. Build agent architectures, tooling, retrieval/memory, and evaluation pipelines with rigorous statistical benchmarking. Optimize prompts and inference, collaborate with engineers to productionize prototypes, and drive research on agent planning, safety, and reliability.

As a Data Scientist at SentiLink, you'll develop fraud detection models using machine learning, engage in product development, and support analysis across teams. This role emphasizes hands-on technical work and end-to-end project ownership in a fast-paced environment.

The Data Scientist will analyze user behavior, create segmentation strategies, design experiments, and track business metrics to drive growth in a SaaS company.

As a Data Scientist, you will develop algorithms, collaborate on product requirements, and communicate data-driven insights, while enhancing product offerings and delivering actionable insights.

The Data Scientist 1 role involves cleaning and analyzing complex datasets, developing statistical models, and communicating insights through data visualizations. Responsibilities include collaborating with teams, maintaining data quality, and keeping up with advancements in the field.

As a Staff Data Scientist at SentiLink, you will develop fraud detection models, conduct analyses, collaborate across teams, and drive the development of financial risk products.

Lead end-to-end data science projects, develop machine learning models, collaborate with stakeholders, mentor team members, and communicate insights effectively.

As a Senior Data Scientist, you will collaborate with cross-functional teams to drive AI/ML product development, analyze user data, and influence product strategies.

Own and evolve revenue calibration models tying CX interactions to revenue, design causal inference and experimentation frameworks, build LLM-powered classification/NLP pipelines, productionize models with Analytics Engineers, define segmentation and behavioral signals, and ensure statistical rigor for executive reporting and regulatory defensibility.

Lead development and deployment of predictive models, analytics, and dashboards to support Sales, Marketing, Customer Success, and GTM operations. Mentor data scientists, partner with business leaders to prioritize analytics, ensure data governance and quality, and present insights to executives. Work with Snowflake/data lakes, build scalable ML solutions, and drive analytics adoption across the enterprise.

Develop prototypes, PoCs, and MVPs for GenAI solutions. Apply deep learning and ML principles using Python, Hugging Face, LangChain, OpenAI API, TensorFlow/Keras/PyTorch, and cloud model services. Work with multi-modal data and intelligent agent tools. Be self-motivated, collaborative, and focused on solving hard AI/GenAI problems.

Customer-facing data scientist advising customers on experiment design, statistical methodology, and experimentation architecture; running and analyzing A/B tests; building scalable experimentation programs; creating repeatable frameworks and technical enablement; partnering with Sales, Solutions Engineering, Product, and Engineering to drive customer success.

The Staff Data Scientist will advance machine learning models to optimize claim audits and improve business outcomes in healthcare.

The Staff Data Scientist will lead the development and deployment of ML and GenAI systems to detect billing errors and fraud in healthcare payments, collaborating with cross-functional teams.

As a Data Scientist at Sardine, you'll design and deploy data-driven solutions to prevent fraud, collaborating with clients and engineering teams to build and optimize machine learning models.

The Data Scientist will develop tools for enhancing signature management capabilities, integrate diverse data holdings, and leverage AI/ML solutions for operational support.

Develop a tool to enhance signature management capabilities and integrate diverse data holdings, leveraging AI/ML solutions to meet operational needs.

The Data Scientist II role involves developing scalable analysis frameworks, building monitoring systems, enhancing data pipelines, and facilitating model improvements for customer success while collaborating across teams.

Perform statistical analysis, predictive modeling, and data visualization on workforce and training data. Build dashboards, produce ad hoc analyses and decision-support products, advise on data governance/privacy, and collaborate with stakeholders to define metrics, deliverables, and reproducible analytic workflows.

Use statistical and causal inference methods to build, implement, and monitor marketing models (Bayesian MMM, multi-touch attribution), analyze A/B and uplift tests, partner with marketing to test and drive data-informed decisions from large web-product datasets.

The Data Scientist will build predictive models, drive forecasting, design experiments, and translate findings for stakeholders, optimizing healthcare operations.

Lead the technical development and automation of enrollment forecasting models, collaborating with various departments to enhance decision-making and forecast accuracy.

The Forward Deployed Marketing Data Scientist will work with AI customers and engineering teams to optimize AI-driven marketing campaigns through data analysis, diagnostics, and communication of insights to stakeholders.