Top Remote Machine Learning Jobs in San Antonio, TX

The Analytics Lead will leverage data analytics to optimize credit strategies, monitor portfolio performance, and collaborate on credit policy with stakeholders across technical and non-technical teams.

Use advanced analytics and ML to design and monitor credit risk models, optimize underwriting and credit strategies, partner with Engineering/Product/Compliance, oversee portfolio performance and regulatory alignment, and lead cross-functional initiatives to balance growth, compliance, and risk mitigation.

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.

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.

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.

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

Lead client-facing Data & Analytics engagements across pre-sales, architecture, and delivery. Define strategy, roadmaps, solution designs, and SOWs for modern data platforms, pipelines, governance, analytics, and AI enablement. Drive practice development, create reusable IP, mentor teams, and ensure quality delivery and strong business outcomes.

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.

Lead design, implementation, and scaling of enterprise Palantir data solutions. Oversee cross-functional teams to build data pipelines, integrations, governance, and advanced analytics (ML/AI). Manage project delivery, stakeholder engagement, performance optimization, and mentor senior engineers and analysts while ensuring security and regulatory compliance.

Licensed MD applies clinical expertise to extract, model, validate, and maintain clinical relationships for a healthcare knowledge graph. Works with data scientists and SMEs to build training datasets, support CDS product development, ensure clinical accuracy, and provide analytics and evidence-based insights to improve search, discovery, and point-of-care workflows.

As a Senior Impact Analyst, you will analyze sustainability challenges, design and manage interventions, and work closely with smallholder communities, emphasizing rigorous research and collaboration.

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 an Associate Engineer in Data Science, you will leverage data analysis and machine learning to solve complex problems and develop inspiring digital products.

Lead fraud detection and mitigation for a conversational BNPL product. Define fraud typologies, own repayment and chargeback analytics, manage fraud KPIs, design operational policies, collaborate on ML models and decisioning workflows, and coordinate SARs and compliance reporting.

Lead fraud risk for a conversational lending product (SNPL): define first-party fraud typologies, analyze repayment and chargeback trends, own fraud KPIs, design automated/manual blocking policies, coordinate ML/rules with central Fraud and Data teams, and liaise with Compliance on SARs and loan abuse.

As a Credit Risk Senior Analyst at Marqeta, you'll lead underwriting strategies, refine credit policies, conduct risk analyses, and present findings to senior management.

The Data & Analytics team at Surescripts transforms healthcare data into actionable insights, collaborating with various stakeholders to support critical decisions across the healthcare ecosystem.

Lead payments analytics by building scalable reporting, causal inference and ML models, designing experiments, partnering with product/engineering/finance to optimize payment processing, reconciliation, and settlement, and translating results into executive recommendations to drive global payments improvements.

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.

Design, build, and automate scalable batch and streaming data pipelines, implement data models and ETL, automate deployments, support ML/experimentation, maintain server architecture, and partner with stakeholders to deliver analytics and data-driven tools.

Lead marketing analytics and root-cause investigations across the B2B SaaS funnel. Maintain data integrity and dashboards, monitor integrations (Marketo, Salesforce, 6Sense, Snowflake), quantify impact of trends, and recommend corrective actions. Architect and train AI/agent-driven analytics (Ask Anything), build semantic layers in Sigma/Snowflake, validate agent outputs, and partner with Revenue Marketing and Strategy teams to drive data-backed decisions and mentor junior analysts.

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.

Support analytics by cleaning, validating, and transforming data; build dashboards and KPI reports; perform trend, cohort, and A/B testing analyses; improve data pipelines and forecasting; present insights to cross-functional teams.