Top Remote Machine Learning Jobs in San Antonio, TX

The Risk Analyst will develop strategies to mitigate fraud risk, analyze data, and collaborate with various teams to support low friction customer experiences. Responsibilities include reviewing accounts, creating analytical models, and reporting on progress against business goals.

Lead the development and implementation of automation techniques using AI and machine learning to improve life underwriting operations and processes.

Lead deep-dive analyses into account takeover and fraud, design and implement real-time defenses, collaborate with product/engineering/data science, run incident response, and deliver actionable insights to protect users while preserving UX and core metrics.

As a Senior Data Scientist, you will analyze data, build models, and collaborate with teams to enhance credit evaluation using machine learning.

The role involves managing a client portfolio of Chief Data Officers, delivering insights on data strategy and analytics, mentoring clients, and fostering collaboration with internal teams to ensure client satisfaction and retention.

Lead the ML Data Enablement team to define strategy and execution for accelerating third-party and internal data onboarding, enforce data quality and SLAs, build metadata and lineage standards, and deliver scalable data infrastructure and workflows to reduce time-to-production for ML models.

Lead marketing data science efforts, overseeing analytics and machine learning strategies to enhance user acquisition, engagement, and retention. Mentor a team and communicate data insights to executives to influence marketing and budget decisions.

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 Staff Advanced Analyst will drive data analytics to improve CS Safety experiences, influence product decisions, and build measurement tools using data-driven insights.

The Business Analyst 2 analyzes AI-powered data solutions, optimizes customer experience automation, and collaborates with teams to drive business insights and value.

As a P&C Actuary, you will assess risks for insurers, support audit teams, and maintain compliance with regulations, while growing client relationships and improving tools for efficiency.

As an AI Engineer, you'll work closely with customers to understand their needs, train and deploy models, and build scalable AI systems.

Design, build, and maintain forecasting and portfolio optimization models for U.S. power markets; analyze market outcomes, track supply/demand/congestion dynamics, and apply statistical, optimization, and ML methods to inform commercial decisions.

Lead content programming through analysis, classification, and editorial judgment. Monitor performance, synthesize query analysis, propose product improvements, curate content, and collaborate with Engineering/Data Science on LLM/ML/NLP initiatives.

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

Join Nextdoor's machine learning team to build data-intensive products, develop ML models, analyze datasets, and enhance user experiences. Collaborate closely with product and data science teams.

Lead development and execution of data-driven audit strategies for insurance and PBM clients. Analyze large datasets, design analytics solutions, create dashboards, perform statistical profiling and sampling, ensure regulatory compliance, manage project budgets and client communications, and coach junior staff to improve examination efficiency and effectiveness.

Lead data acquisition and management strategies for AI models, analyze data systems, oversee partnerships, and guide a team in optimized data usage.

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.

Lead the Data & Analytics team, focusing on building data platforms, improving delivery speeds, and integrating Generative AI into data strategies.

The Data Engineer will build real-time data pipelines for pricing algorithms, collaborate with teams, and contribute to batch data workflows.

Drive measurement, causal inference, and experimentation to optimize content promotion and personalization. Build robust metrics, partner with product and engineering, surface discovery opportunities, and independently deliver high-impact analytics and ML solutions.

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.

Build and maintain dashboards and reports (Excel, Tableau, Sigma) by pulling and modeling production data (SQL, Python). Create pricing models for RFPs, define operational and financial metrics, optimize queries and data structures, run A/B experiment analyses, and partner with business leaders to generate insights and recommendations to improve roadside assistance operations and performance.