Top Senior Machine Learning Jobs in Richmond, VA

Build and validate statistical and machine learning models for credit card loss forecasting, modernization, and allowance (CCAR). Partner with data scientists, engineers, and product managers to transform data, automate insights, support model governance, and present model risk impacts to executives using cloud and big-data tools.

Lead development of machine learning and NLP solutions for operational risk analytics: partner with cross-functional teams, build end-to-end models (design, training, evaluation, validation, implementation), analyze large numeric and text datasets, deliver insights and reporting to senior leaders, and experiment with emerging generative AI techniques to improve risk management.

The Distinguished Engineer will drive innovation in banking technology, lead software engineering projects, mentor teams, and utilize AI and advanced architectures for risk management.

The Senior Associate, Data Scientist will partner with cross-functional teams to identify risks associated with models and validate machine learning models across the enterprise, enhancing decision-making while ensuring model governance and risk management.

Lead and grow a full-stack engineering team delivering cloud-native, microservices-based risk management solutions. Collaborate with product managers, mentor engineers, oversee architecture and delivery, and occasionally contribute code. Drive adoption of modern cloud, container, and AI/ML technologies to build scalable, compliant systems.

Lead and deliver advanced analytics and machine learning solutions to support pricing, revenue optimization, and partner relationships. Collaborate with cross-functional teams to design, validate, and implement models at scale using large transaction datasets and modern big-data tooling. Translate technical insights into actionable business recommendations.

Owner of product features for Card Intelligence ML initiatives; collaborate with data scientists, engineers, and stakeholders to define roadmaps, break down epics into MVPs, prioritize features, and accelerate model-to-market delivery for fraud prevention.

Lead and scale a Card risk assessment team, drive transformation of assessment programs (PLA, RCSA, risk inventory), integrate AI/ML and data analytics for continuous risk insights, advise stakeholders and regulators, and develop talent while improving processes and cross‑functional alignment.

Lead technical vision and hands-on engineering for Capital One's Global Payment Network. Design and deliver high-throughput, low-latency distributed systems in the cloud, drive AI-native automation, mentor engineers, influence executives, and improve performance, reliability, and security across payment platforms.

The Compliance Testing Manager ensures regulatory compliance through quality assurance of testing processes, mentoring teams, and collaborating with business areas while managing risk-based compliance transactions.

Lead the In-Vehicle Experience team at Samsara, focusing on transforming in-cab cameras into intelligent companions. Collaborate with engineering, prioritize features, and ensure client interactions highlight trust and connection. Conduct customer research and integrate AI and ML into product features.

Lead corporate communications strategy and execution: own product and model launches, media and executive communications, narratives, social presence, and major company moments. Translate technical research and product advances into compelling stories for developers, enterprise buyers, partners, and analysts. Partner cross-functionally with CEO, CMO, product, brand, and demand gen to build credibility and influence in the voice AI ecosystem.

Lead multiple product-focused engineering teams to design, build, deploy, and modernize risk-management software using full-stack technologies, microservices, AWS, Big Data, and ML; mentor engineers, improve engineering practices, and drive migration from monoliths to scalable services.

Lead design and implementation of Headway's insurance systems (eligibility, pricing, matching, claims). Build data-intensive, ML-powered platforms and automation, mentor engineers, write high-impact code, and improve accuracy and reliability across state and payer complexity to scale insurance-covered therapy.

Lead CrowdStrike Finance & Accounting AI transformation: define operating model and governance, prioritize AI use cases, oversee POC-to-production delivery, drive enablement and change management, measure benefits realization, and report outcomes to executives.

Lead deployment, configuration, optimization, and operational support of CrowdStrike Falcon AI/ML detection and response capabilities. Tune ML models, build automation playbooks, develop scripts using Falcon APIs, integrate AI features with customer toolchains, support incident response and threat hunting, deliver customer workshops, and mentor team members. Travel up to 25%.

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.

Manage and mentor a global team of data engineers and data scientists, align technical delivery with business goals, allocate resources, improve delivery processes, drive automation and technical evangelism, and collaborate with sales and account teams to support growth.

Lead AI engineering teams to design, build, and deploy end-to-end AI solutions. Manage client relationships, plan and deliver projects, mentor staff, drive adoption of cloud-native microservices, CI/CD, vector databases and orchestration tools, and ensure high standards of quality, innovation, and compliance.

Lead the development of fraud prediction models using machine learning, collaborating across teams to build, scale, and monitor models in production.

Lead a team of ML engineers to develop fraud detection models, defining strategies, driving model evolution, and ensuring effective integration with cross-functional teams.

Lead and architect high-value healthcare analytics engagements, build reusable analytic frameworks (DBT), partner with product and engineering, mentor analysts, ensure analytic quality, and represent Arcadia externally to drive population health and value-based care outcomes.

The Senior Product Manager will oversee the strategy and development of telematics data products, manage cross-functional teams, and ensure product viability and market alignment through customer insights and technical fluency.

Review and audit machine learning models and model risk practices across the enterprise. Partner with cross-functional teams to design, train, evaluate, validate, and implement ML and NLP solutions, using tools like Python, Spark, H2O, and AWS. Translate technical findings into business recommendations and assurance for stakeholders and the Audit Committee, while researching and applying emerging Generative AI and state-of-the-art methods.

You will tackle AI challenges, develop scalable software and collaborate with teams to enhance healthcare navigation using AI solutions.