Top Machine Learning Jobs in Columbus, OH

Lead teams applying advanced data science and machine learning to large-scale claims, clinical, and member data to generate actionable insights that reduce cost of care and improve population health. Manage client relationships, mentor staff, ensure project delivery and quality, develop payer-focused analytics products, present findings to senior stakeholders, and promote continuous improvement and knowledge sharing.

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 Research Engineer will collaborate with scientists to develop and validate machine learning models for speech technologies, manage scalable training systems, and design tools for accessibility to non-technical users.

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.

The Staff ML Engineer will design and operate Samsara's ML platform, collaborating with teams to enhance ML features and improve safety outcomes. Responsibilities include overseeing system reliability, leading technical direction, and mentoring engineers.

Lead control and risk management activities within Consumer & Community Banking. Partner with stakeholders to identify gaps, design and implement control strategies, use automation/AI/data analytics for monitoring, own Risk & Control Self-Assessments, drive regulatory compliance projects, and recommend improvements using digital risk management and agile practices.

Lead market risk oversight for Real Estate funds in Alternatives: measure and analyze market, liquidity, performance and counterparty risks; implement and improve risk frameworks, controls, and reporting; conduct deep dives on emerging risks; collaborate with investment and control teams and escalate issues to senior management.

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

Lead and transform the Fraud Intelligence Team into a high-impact function by improving operating models, QA, tooling, and metrics; build entry-level talent programs; connect labeling to measurable fraud prevention outcomes; deliver actionable insights to Product, R&D, Analytics, and GTM; and leverage AI and automation to increase productivity and business impact.

Partner with functional leaders to translate business strategy into people strategy. Own org design, performance management, compensation, talent development, engagement, and retention. Provide coaching on career pathing, change management, and sensitive employee issues. Use people data to generate insights and recommendations, build compliant HR policies, manage global employee relations, and collaborate with People Team COEs to deliver cohesive people programs at scale.

Serve as second-in-command for Coinbase Derivatives' Market Regulation Department, leading day-to-day regulatory compliance, managing exams and audits, advising on CFTC Core Principles, reviewing surveillance escalations and enforcement actions, and coordinating cross-functional regulatory workstreams to ensure the DCM meets obligations and resolves findings timely.

Lead strategy and a portfolio of initiatives to drive advisor conversion and productivity using data, experimentation, and AI. Prioritize opportunities, define success metrics, translate needs into analytics/technology requirements, drive cross-functional delivery, and measure post-launch impact.

Provide legal guidance on Rubrik's AI use and products, ensuring compliance with laws and contracts, drafting and negotiating AI terms, coordinating generative AI review processes, educating employees, and improving AI review controls and workflows across cross-functional teams.

Lead cybersecurity architecture for cloud-native enterprise solutions: evaluate controls and new technologies, advise stakeholders, provide technical guidance, promote firmwide SDLC practices, and mentor peers to mitigate risk and adopt strategic solutions.

Nine-week summer analyst program within Operations supporting processing, trade/asset support, reporting, transformation, and data management. Responsibilities include transaction processing, reconciliations, client lifecycle support, data analytics and reporting, risk reporting, process improvement, and creating Tableau dashboards. Program includes training, networking, and may lead to full-time roles.

Lead risk and control efforts for Business Banking Lending products by identifying gaps, designing controls, leveraging automation/AI and analytics, conducting RCSA walkthroughs, driving remediation projects, and partnering with stakeholders to ensure regulatory compliance and continuous improvement.

Lead adoption of agentic AI across product teams by coaching, prototyping, and embedding new AI-enabled workflows. Redesign operating models, translate AI concepts into playbooks and learning paths, measure adoption and impact, and partner with leaders to scale responsible AI practices across product delivery in a large regulated banking environment.

Lead strategy, implementation, and scaling of AI-powered coaching agents across the firm. Own end-to-end product lifecycle, benchmark emerging AI tech, collaborate with cross-functional teams, ensure governance/compliance, track performance, and produce technical documentation and roadmaps.

Lead design and build of scalable, secure AI/LLM-based production systems and frameworks; develop reusable tooling, evaluation and quality mechanisms; review code; guide cross-functional teams; design multi-step AI workflows and integrations; present technical recommendations to senior leaders.

Own end-to-end product lifecycle for a global entity data platform: resolve organization records into a trusted "golden profile," drive roadmap and backlog, define success metrics (precision/recall, throughput, completeness), enable explainable ML-assisted matching, manage third-party data onboarding, and partner with engineering, ML, governance, and business teams to deploy production-grade, auditable data products at scale.

Design and implement enterprise cybersecurity architecture for cloud-native applications. Embed security across SDLC and CI/CD, build Python automation for monitoring and remediation, evaluate vendors, lead practice communities, and collaborate with risk and compliance to translate regulatory requirements into technical controls while validating AI-assisted security outputs.

Apply advanced quantitative and computational methods to build and deploy machine learning, optimization, and statistical models on large structured and unstructured consumer data. Drive full modeling lifecycle from problem definition to communication of results and recommendations, present findings to senior stakeholders, and act as a subject-matter expert while contributing new ideas to the team.

Lead cybersecurity architecture for cloud-native applications within consumer banking: define target state, assess risks, propose mitigations, drive automation, lead vendor evaluations and communities of practice, and communicate solutions to senior stakeholders.

Build and validate ML, optimization, and statistical models on large structured and unstructured consumer datasets; generate insights and actionable recommendations; communicate results to senior stakeholders; contribute across the full modeling lifecycle and advance team knowledge.