Top Data Science Jobs in Houston, TX

Lead analytics initiatives to deliver strategic insights for consumer markets. Develop advanced analytics and BI solutions, manage teams, engage stakeholders, implement cloud analytics, and coach diverse teams to improve performance and decision-making.

Lead research and engineering of production-grade LLM/GenAI systems for cybersecurity: design models and architectures, drive data labeling and evaluation, collaborate with product and engineering to deploy scalable solutions, mentor data scientists, set technical strategy, and advance AI safety, red-teaming, and applied ML innovations for detection and operational use.

Lead advanced analytics and ML efforts to extract insights from large-scale historical data, design features and data representations for models and LLM/agentic systems, partner with product and engineering to build data pipelines and prototypes, evaluate AI workflows, and drive innovation through experiments and empirical analysis to inform product strategy.

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.

Build and productionize end-to-end fraud and financial risk models: data acquisition, feature engineering, labeling, training, experimentation, deployment, and monitoring. Research new fraud types, drive product development, support data quality and access, and present analyses to inform product, operations, sales, and marketing.

Lead product analytics efforts by designing and evaluating experiments, building dashboards, and producing statistical insights. Partner with product, design, and engineering to measure product success, identify optimization opportunities, and embed ML-driven personalization into the product.

Build and deploy statistical and machine learning models for the Toast platform. Collaborate with product, engineering, and business teams to identify opportunities, develop data-driven solutions, evaluate models, and communicate insights to stakeholders. Work in a fast-paced environment and contribute to production ML systems and experimentation.

Lead design and delivery of scalable ML systems across the full lifecycle for recommendations, demand forecasting, targeting, and personalization. Collaborate with engineers, product, and stakeholders to set architecture, metrics, and production best practices; mentor data scientists; lead experimentation and deploy/monitor models using cloud and MLOps tooling.

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.

Lead complex modeling projects combining deep learning, LLMs, and traditional techniques. Prototype, deploy, and monitor production models, mentor data scientists, collaborate with engineering/product, and translate results into business impact for insurance customers.

Lead teams applying advanced data science and machine learning to large-scale claims, clinical, and member data to generate actionable insights that reduce cost of care and improve population health. Manage client relationships, mentor staff, ensure project delivery and quality, develop payer-focused analytics products, present findings to senior stakeholders, and promote continuous improvement and knowledge sharing.

Design, research, and deploy NLP/GenAI surveillance models (LLMs, RAG, knowledge graphs) to detect suspicious financial behavior; build production-ready systems, collaborate with Compliance/Legal/IT, and drive adoption of AI solutions.

Lead end-to-end pricing experimentation and strategy for consumer and business products. Design and analyze A/B tests, build pricing models and production-grade data pipelines, partner cross-functionally, and present actionable recommendations to senior leadership.

Lead design and evolution of large-scale nodal power market models. Define mathematical approaches, develop optimization/forecasting methodologies (MILP, SCUC/SCED), collaborate with engineers to productionize models, work with product and customers to translate market problems into software, mentor data scientists, and guide long-term product strategy.

Seeking a SAS Data Scientist with at least 1 year of SAS experience and some background in data analytics. Full-time position in Houston.

Perform epidemiologic analyses on surveillance, clinical, claims, lab, and survey data; develop analysis plans, statistical methods, and technical reports; build dashboards and automated analytic workflows; design data quality rules and surveillance indicators; translate findings for diverse stakeholders; support public health reporting, manuscripts, and dissemination; mentor junior staff and provide technical assistance.

Develop statistical, geospatial, and machine learning models to improve underwriting and portfolio management. Build reusable data pipelines, automated workflows, software applications and APIs, analyze spatial/exposure/catastrophe data, and mentor junior team members to support pricing, underwriting, and risk management.

Lead quantitative analysis and modeling of large real-world health datasets to estimate disease prevalence and incidence. Design statistical and machine learning models, build data pipelines and dashboards, ensure reproducibility and data quality, collaborate with public health experts, and prepare scientific reports and presentations.

The Senior Data Scientist partners with Customer Success to perform deep-dive analyses, diagnose metric shifts, build predictive models (churn/upsell), apply causal inference and experimentation, measure business impact, and develop AI/LLM solutions. Responsibilities include self-serving across the data stack for extraction, pipelining, and dashboards, defining KPIs, and delivering actionable insights to reduce churn, drive revenue, and improve operational efficiency.

Lead development and deployment of large-scale LLM and GenAI solutions for cybersecurity. Drive research strategy, model training, evaluation, safety/red-teaming, and cross-functional productization. Mentor data scientists, set technical standards, and represent the team through publications and thought leadership.

Lead epidemiology and surveillance programs, directing multidisciplinary teams to develop surveillance datasets, analytic products, dashboards, and reports. Provide scientific leadership on epidemiologic methods, statistical modeling, data quality assurance, and interpretation. Advise clients, support data modernization and AI-enabled analytics, lead dissemination and thought leadership, and contribute to business development and contract-dependent work.

Lead strategy, development, and production deployment of scalable AI/GenAI and ML solutions. Drive technical direction, mentor data scientists, own end-to-end initiatives, ensure MLOps and model governance, collaborate cross-functionally, and deliver measurable business impact using advanced models (LLMs, transformers, diffusion) and cloud platforms.

Support data analysis, prepare data for exploratory analysis, contribute to model building and validation, assist metadata and ETL tasks, and create visualizations to communicate model insights.

Entefy seeks a Senior Data Scientist with a Master's or PhD in a relevant field, and 3+ years of experience. Responsibilities include delivering advanced analytics, leading teams, and extracting insights from datasets.

Build and productionize ML systems for personalization, search, and recommendations. Apply statistical and ML models using Python and SQL, collaborate with stakeholders, and measure business impact across cloud environments.