Top Senior Machine Learning Jobs in San Antonio, TX

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 Manager, Growth Analytics & Marketing Science will build and evolve marketing measurement frameworks, drive analytics, and optimize marketing strategies through data and AI.

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.

The role involves leading the enterprise strategy for data analytics and technology modernization, driving data-driven decision making, and managing digital transformation initiatives while building a high-performing team.

The Quantitative Researcher will execute project work, apply rigorous quantitative methods, lead data collection and analyses, and communicate findings to stakeholders.

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 and implement credit strategies using data, machine learning, A/B testing and advanced analytics to optimize underwriting, pricing, and credit line decisions. Lead end-to-end analytics for credit card products, monitor portfolio performance, conduct root-cause analysis, partner cross-functionally, and communicate findings to stakeholders.

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

As the Director of Measurement Strategy, you will define the analytics roadmap, manage client relationships, lead analytics projects, drive revenue growth, and develop your team while ensuring high-quality analytics delivery.

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

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.

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 Data Product Manager - Curation designs and manages curated data products, overseeing data modeling, governance, and partnership with analytics teams to enhance data usability and support advanced analytics, including Machine Learning.

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.

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.

The Sr. Data Engineer will architect and build an end-to-end data platform, developing data pipelines and infrastructure for AI and robotics teams, ensuring data integrity and governance, and collaborating on ML model development.

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.