Top Senior Machine Learning Jobs in Hartford, CT

Lead the development of machine learning systems for Cedar Pay's Personalization Engine, manage ML engineers, and ensure ML model effectiveness.

The Staff Machine Learning Engineer will lead ML initiatives, develop ML systems, collaborate with cross-functional teams, and mentor junior engineers to optimize healthcare intake workflows using advanced machine learning techniques.

Lead and transform the Fraud Intelligence Team by designing scalable operating models, QA and measurement frameworks, and talent programs. Drive labeling quality, operational metrics, and fraud prevention impact; convert frontline fraud observations into insights for Product, R&D, Analytics, and GTM; leverage AI, automation, and tooling; and serve as a cross-functional fraud subject-matter expert while developing early-career talent and measurable business outcomes.

The role involves deploying and supporting CrowdStrike's AI capabilities in cybersecurity, optimizing threat detection, and mentoring teams on AI solutions.

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

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.

Manages healthcare analytics, business intelligence, dashboards, KPIs, reporting, data validation, root cause analysis, and performance measurement supporting medical policy and payment integrity. Partners with clinical, finance, compliance, technology, quality, and reporting teams to improve affordability, operational quality, governance, compliance readiness, and process efficiency. Coordinates analytical projects, develops business requirements, monitors data quality, and presents actionable insights to leadership.

Lead a small team to design, build, deploy, and monitor ML/AI solutions for Claims (fraud, triage, severity, litigation, subrogation). Manage projects, collaborate with engineering and IT, follow model governance, and mentor staff.

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 the vision, strategy, roadmap, and lifecycle of data science products and platforms. Translate business needs into technical requirements, prioritize backlogs, collaborate with data scientists and engineers, track KPIs, conduct market and customer research, and champion agile delivery. The role also serves as a liaison across stakeholders, mentors junior product professionals, and drives data-informed product improvements.

Leads advanced data science and analytics initiatives using statistics, modeling, machine learning, and business analysis. Develops scalable policy-adherence metrics and valuation models using complex structured and unstructured healthcare data, including claims and denials. Creates reports, projections, and presentations; advises executives; manages stakeholders; and influences roadmap and implementation decisions across compliance, contracting, Medicaid, and business teams.

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.

Build predictive and cohort models supporting underwriting and marketing. Source, evaluate, combine, and analyze internal and external data; develop analytical datasets and solutions; implement and monitor models in production; communicate insights to business partners; document methodologies and results; and support statistical analysis requests. May supervise 1–2 analysts and provide guidance on cohort modeling and related analytics techniques.

Lead technical direction and deliver large-scale ML platform infrastructure including feature store, model serving, experimentation, and training pipelines. Drive architecture, mentor engineers, coordinate cross-team initiatives, resolve system-wide issues (latency, reliability, GPU utilization), and define safe ML deployment paths from registration through rollout, monitoring, and rollback.

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.

Lead assessment and secure adoption of AI/ML and GenAI systems for clients. Design security patterns and controls, perform assessments and pen tests, prototype AI-enabled security capabilities, ensure compliance (PII, privacy, regulatory), document protocols, and collaborate with cross-functional teams to productionize scalable AI-security solutions.

Leads and manages an applied machine learning team developing fraud detection and identity verification models. Responsibilities include people management, coaching, code review, production ML systems, model lifecycle ownership, experimentation, deployment, monitoring, fraud research, cross-functional prioritization, and communicating results. The role remains hands-on while partnering with Product, Engineering, Risk, and leadership to drive measurable business impact and shape future product strategy using machine learning and AI.

The Senior Data Scientist will analyze data to drive product strategy, optimize performance, and support product launches, collaborating with cross-functional teams.

Design and deploy machine learning models for financial document processing, optimize large language models, collaborate with cross-functional teams, and guide junior peers in a fast-paced environment.