Top Senior Data Science Jobs in Louisville, KY

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.

As a Senior Data Scientist, you will design and deploy machine learning and graph algorithms to enhance identity trust solutions, own end-to-end projects, and collaborate with product and engineering teams to improve KYC and compliance products.

The Principal Data Scientist will lead measurement strategy for Zillow's advertising business, focusing on ad performance, experimentation, and data-driven decision-making to drive revenue growth and advertiser value.

Lead the design and deployment of machine learning and graph-based systems for international identity verification, ensuring compliance and addressing regional challenges.

The Senior Data Scientist will design ML-based entity resolution systems, build and refine NLP and ML models, and translate model results into business impact while supporting data strategy and improving data pipelines.

The Senior Data Scientist in Conversational AI & NLU designs and optimizes AI solutions, evaluates models, collaborates with stakeholders, and analyzes conversational data to improve user experience.

Lead the development and deployment of advanced ML/AI products, mentoring teams and collaborating with stakeholders to influence business outcomes.

The Senior Manager, Data Science & Analytics will lead a team to drive analytics and experimentation strategies for Yahoo Mail's growth and monetization, engaging with product, finance, and marketing to transform data insights into actionable strategies for success.

The Sr. Data Scientist will design, develop, and deploy AI models and tools, mentor teams, and drive data-driven insights while collaborating with cross-functional teams.

The Senior Data Scientist at Fetch will develop and scale data science capabilities, architect predictive models, and influence product strategy through collaboration and experimentation. They will lead initiatives focused on engagement, churn, and business impact measurement using advanced analytics and machine learning tools.

The Senior Data Scientist will develop machine learning models, conduct A/B tests, and work with behavioral data to enhance customer engagement and partner ROI.

Lead data science for Yahoo Mail subscriptions: analyze acquisition, conversion, pricing, retention, and churn; design and analyze A/B and multivariate experiments; build predictive and clustering models; partner with product, engineering, design, and business teams to deliver data-driven growth and monetization insights.

Develop and prototype learning-based models using data-centric techniques; design and maintain multi-modal data and feature extraction pipelines; build auto-labeling systems; perform ETL and optimize SQL for analysis/ingestion; collaborate with data infrastructure and ML engineers to integrate workflows; write maintainable code and participate in code reviews to support scalable ML production.

Seeking a Senior Data Scientist to lead predictive analytics and machine learning initiatives. Responsibilities include building ML models, data management, and mentoring junior data scientists. Must have expertise in AWS and strong statistical knowledge.

As a Principal Data Scientist, you'll design and deploy cutting-edge machine learning models to drive financial success for customers and guide technical teams.

The Principal Data Scientist will design, develop, and deploy machine learning models, innovating methodologies and collaborating across teams to enhance financial decision-making and risk management.

Lead development and operationalization of measurement products (MMM, incrementality, insights, recommendations). Build, deploy, and maintain production-grade statistical and ML systems, debug end-to-end data and model issues, evaluate methodologies, and partner with engineering, product, and customer teams to improve measurement accuracy and reliability. Provide customer-facing explanations and support for measurement outputs.

Build and deploy credit and fraud risk models using advanced ML/statistical methods. Partner with stakeholders, extract insights from large transaction datasets, automate feature/production pipelines, mentor junior data scientists, and ensure model quality and deployment scalability.

Lead the development of AI solutions and systems to improve healthcare outcomes, managing data science strategies and collaborating with engineering teams.

Proactively explore RevenueCat's data to identify product opportunities, translate ambiguous problems into analyses and production-grade predictive/descriptive models, partner with Product and Engineering to ship data-powered features (LTV prediction, experimentation, benchmarking), define statistical approaches, iterate on models in production, and communicate insights to technical and non-technical audiences.

The Lead Data Scientist will drive AI innovation, manage data science strategies, build AI systems, and collaborate on scalable AI solutions for healthcare delivery.

The Senior Data Scientist will integrate data from various sources, analyze web performance, and provide insights for strategic decision-making. Responsibilities include developing automated systems for content coverage, tracking metrics, and designing experiments to assess new initiatives' impact.

The Senior Data Scientist will manage data collection, design study protocols, train juniors, lead report development, and support innovative analytics tools.

The Senior Data Scientist oversees data collection and preparation, designs study protocols, leads report development, trains junior employees, and manages project workstreams while collaborating with team members to optimize business performance.

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.