Top Senior Machine Learning Jobs in San Antonio, TX

The Data Management/Governance Specialist will develop frameworks, ensure compliance with data policies, establish quality standards, and provide training on governance best practices.

Manage a team of data scientists to develop fraud detection models, lead planning and collaboration with leadership, and communicate outcomes effectively while maintaining strong business intuition and technical leadership.

Lead revenue assurance: monitor and audit billing pipelines, build data pipelines and models (Databricks, Python, SQL), detect and prevent revenue leakage, run experiments, define metrics, and partner cross-functionally to protect and optimize subscriber revenue at scale.

As a Senior Machine Learning Engineer, you'll build and deploy ML models for risk and fraud detection, leading technical efforts and collaborating cross-functionally.

Contract role combining actuarial science, risk management, and AI to improve portfolio performance. Responsibilities include loss and combined ratio analysis, portfolio risk assessment, catastrophe and exposure modeling, stress testing, and integrating ML to enhance pricing, reserving, and risk selection while collaborating with underwriting, finance, and product teams.

The Director of Statistics leads statistical initiatives in phase 3b/4 and RWE studies, provides expertise in HTA and regulatory compliance, and collaborates with cross-functional teams. Responsibilities include statistical analysis plans, Bayesian methodologies, and mentoring junior staff.

Design, build, and deploy end-to-end data science solutions for pricing, underwriting, claims, and operations. Perform analyses on structured and unstructured data, develop and monitor ML models, create dashboards and visualizations, implement data pipelines, and collaborate cross-functionally to prioritize analytics initiatives and communicate results to technical and non-technical stakeholders.

Lead the Decision Science function, designing ML models, overseeing experimentation frameworks, and ensuring model adoption across the company, driving operational and commercial improvements.

Lead a team of analysts to advance fraud and safety operations through analytics, ensuring robust data products and compliance while empowering stakeholders with actionable insights.

The Senior Data Scientist will design and deploy time-series forecasting models, collaborate with stakeholders, and operationalize models in cloud environments, focusing on demand planning across various industries.

The role oversees analytical characterization and comparability studies for biologics, ensuring regulatory compliance and leadership in product development.

As a Staff Data Scientist, you will lead product strategy by building predictive models, optimizing matching algorithms, and guiding product innovations in a consumer tech environment.

As a Principal Data Analyst, you'll leverage machine learning and AI to improve outcomes, manage large data sets, and guide analytics modelers for effective data solutions.

The Senior Manager of Data Insights will lead a team to optimize data sharing and governance, develop data strategies, and deliver actionable business intelligence across Docker's operations.

Serve as an AI/ML-focused solution engineer for Healthcare & Life Sciences: provide technical guidance, design cloud data and lakehouse architectures on Snowflake, lead demos and proofs-of-concept, support sales cycles, collaborate with product and engineering, and communicate AI/ML value to technical and executive stakeholders.

The Manager of RevOps/Yield analyzes patterns and data to optimize ad operations, manage vendor relationships, and oversee a remote team for revenue generation.

The job involves building responsive web dashboards, advanced data visualizations, and analytics tools for unmanned aircraft systems, requiring a deep understanding of UI/UX design and data presentation.

Lead the design and operation of Twilio's ML and data platform, architecting cloud-native pipelines and implementing MLOps best practices while mentoring engineers and collaborating across teams.