Top Senior Data Science Jobs in Houston, TX

Designs, analyzes, and interprets clinical trial, RWE, and observational data for a medical device. Develops statistical plans, predictive models, and ensures data quality, regulatory compliance, and traceability. Collaborates with clinical, regulatory, and data teams, supports submissions and publications, mentors interns, and represents the company externally.

Lead development of foundational marketing ML models (customer intent, next-best-action, marketing mix and attribution). Own model selection, explainability, monitoring, decisioning layers, and translate outputs into actionable recommendations for marketing and product stakeholders while providing technical leadership.

Lead development of Vanta's business analytics function: build scalable product data assets, define measurement frameworks, use AI-assisted analytics, partner with cross-functional teams, and deliver executive-level recommendations to drive product and business decisions.

Design, evaluate, and productionize generative AI/ML solutions (RAG, agents, embeddings, retrieval). Build evaluation frameworks for hallucination detection, benchmark LLMs, optimize prompts/models, create datasets, fine-tune models, and collaborate to deploy and monitor enterprise-scale GenAI systems.

Design, implement, and maintain marketing inference models (e.g., MMM and attribution). Analyze large datasets and A/B/uplift experiments with rigorous statistics, build predictive and causal models, partner with marketing to generate testable ideas, and communicate insights to drive marketing decisions.

As a Staff Data Scientist, you will analyze large-scale broadband data, develop and validate ML models, and integrate solutions into Calix Cloud, collaborating with teams for enhanced network intelligence and subscriber experience.

Lead marketplace measurement, experimentation, and causal analysis; build pricing, recommendation, and retention models; operationalize models with engineering; maintain dashboards and monitor supply-demand balance to guide product and growth decisions.

Lead end-to-end AI/ML initiatives to improve student retention, engagement, and enrollment. Architect and operate data pipelines, feature stores, and production ML systems; deploy, monitor, and automate models; run experimentation programing and measure business outcomes. Mentor team members and set technical standards across Product, Engineering, and CX.

Lead cross-functional teams to identify and implement revenue-driving strategies. Own revenue optimization, develop quantitative analyses (A/B testing, causal impact), improve data pipelines and tracking, embed AI into workflows, and present insights to leadership to scale and recover revenue.

Consult as a fractional data scientist for hedge funds, private equity firms, and family offices. Lead data science initiatives: build infrastructure, develop and deploy models, create portfolio dashboards, monitor post-deployment performance, and partner with investment teams to turn data into actionable investment insights. Advise on vendor selection, data quality, technology stacks, KPIs, and governance.

Design and evaluate predictive and generative models, extract insights from disparate clinical and product data, build and partner on data pipelines, run rigorous evaluations and experiments, and deliver time-sensitive ad hoc analyses to product, engineering, and clinical stakeholders.

Design, build, and deploy LLM-based applications and multi-step AI workflows (retrieval, orchestration, agents) using large-scale structured and unstructured data. Partner with engineering to productionize solutions, implement evaluation and safety measures, ensure compliance and data governance, and communicate results to technical and non-technical stakeholders.

Hands-on senior data scientist splitting work between SQL Server data engineering (ETL, pipeline modernization, data quality) and analytics delivery (Power BI semantic models, dashboards, statistical and predictive modeling). Duties include designing migration options, implementing Python-based cleansing and reproducible analytics, building ETL/deployment processes, responding to ad hoc leadership data requests, and documenting systems for stakeholders. Must obtain VA background/PIV and be a U.S. citizen.

Lead Data Scientist will support advanced analytics, predictive modeling, and machine learning initiatives for clinical decision-making in healthcare. Responsibilities include algorithm design and compliance with VA governance standards.

Design, build, and deploy ML models across diverse use cases; work with managed cloud ML platforms and containerized solutions; collaborate with engineers on production integration and MLOps best practices; preprocess and analyze large datasets; mentor teammates and influence technical direction; translate complex ML concepts for technical and non-technical stakeholders.

Lead end-to-end client ML engagements: scope problems, design, build, and deploy production ML solutions across cloud and containerized stacks. Lead and mentor small teams, manage client relationships, evaluate emerging tools, and ensure models are production-ready and explainable to technical and non-technical stakeholders.

As a Lead Data Scientist, you'll design experiments, build predictive models, and lead a team while shaping data-driven strategies to enhance AI deployments.

Design, develop, and deploy time-series and machine-learning forecasting models (ARIMA, SARIMA, ETS, XGBoost, LightGBM) for demand planning, inventory, and sales forecasting. Perform large-scale SQL data processing, operationalize models in cloud environments (Azure preferred), present insights, and lead client workshops.

The role involves building and validating Marketing Mix Models and geo-experiments, managing measurement infrastructure, and communicating insights to stakeholders.

Design and build custom measurement products by combining Nielsen datasets; develop statistical and ML models; write production-quality SQL, Python, and PySpark; build reusable ETL pipelines; use AI tools and design agentic workflows; translate stakeholder requests, document methodology, and collaborate with Research, Sales, and Insights teams.

Design, build, validate, deploy, and monitor machine learning and generative AI solutions for healthcare and life sciences. Work with EHR, claims, and registry data to produce clinical predictions, operational optimizations, and LLM-powered applications. Translate results for stakeholders, document best practices, and mentor client teams.

Design, develop, and deploy production-grade generative AI and agentic systems (LLMs, RAG, AI agents). Build document intelligence, retrieval pipelines, vector search, and monitoring frameworks. Collaborate with risk, compliance, product, and engineering to deliver scalable, governed GenAI solutions in regulated environments.

As a Senior Data Scientist, you'll lead projects leveraging data to enhance healthcare outcomes, mentor team members, and align data efforts with business goals.

The Senior Data Scientist will analyze and optimize marketing funnels, build statistical models, conduct experiments, collaborate with teams, and mentor junior members.

Design and build predictive models, AI tools, and data visualizations for CMS healthcare initiatives. Analyze quantitative and qualitative data (Medicare claims, public datasets, web analytics), perform feature engineering, anomaly detection, and provide insights to support product design and price-transparency tools. Collaborate with designers, product owners, and engineers in an agile environment.