Top Senior Machine Learning Jobs in Hartford, CT

Own and execute multi-year strategic partnerships with a hyperscaler and an AI lab, aligning technical integrations, commercial motions, and joint go-to-market plans. Coordinate cross-functional teams, run operational cadences, track measurable outcomes (pipeline, ARR, integrations), and represent partnerships to executives while driving hands-on execution and follow-through.

Build and maintain Safari AI’s cloud infrastructure, including production services, system design, reliability, documentation, and security compliance. The role sets technical direction for the cloud stack, collaborates with engineering and operations teams, improves development processes, and delivers incremental features. Candidates should have 4–6 years of software engineering experience, public cloud expertise, and experience taking complex services from concept through production. Streaming processing and machine learning experience are advantageous.

Design, develop, implement, support, and improve financial-system integrations, databases, reporting solutions, and automated processes. Lead technical financial systems projects from requirements gathering through implementation, focusing on Aderant Expert, SQL Server, SSIS, SSRS, and T-SQL. Collaborate with Finance, IS, vendors, and business stakeholders; troubleshoot complex data issues, optimize database performance, document technical solutions, and support multiple concurrent initiatives.

Own Litify’s AI Call Intelligence product line end to end, including call capture, transcription, summaries, conversational insights, voice agents, and agentic workflows. Define the roadmap, quality standards, guardrails, and evaluation practices; lead client discovery, beta programs, competitive research, backlog prioritization, and cross-functional delivery. Partner with engineering, design, data science, and go-to-market teams to launch products, drive adoption, and measure outcomes.

Leads Sophos’s Americas MSP channel strategy, revenue growth, partner productivity, and operating performance. Oversees recruitment, onboarding, enablement, retention, distribution relationships, recurring-revenue forecasting, strategic negotiations, and program optimization. Builds and coaches direct and matrixed teams while influencing product, pricing, investments, and partner-program decisions. Uses performance data and market intelligence to improve activation, adoption, retention, expansion, and return on investment across cybersecurity managed-service offerings.

Lead client-facing AI program governance and delivery as PMO manager. Translate business objectives into AI roadmaps and OKRs, oversee AI/ML lifecycle, ensure data readiness, model validation, deployment, and responsible AI compliance. Manage PMO standards, portfolio prioritization, AI-augmented reporting, and lead executive communications while mentoring PMs, TPMs, and analysts.

Lead a portfolio of technology-enabled continuous improvement initiatives for internal operations and DoD customers. Manage product backlogs, write user stories, define roadmaps, gather requirements, and facilitate Agile, Scrum, SAFe, and PI planning activities. Drive Splunk analytics, dashboarding, alerting, AI, ML, automation, proactive monitoring, and predictive analytics solutions. Ensure stakeholder alignment, measurable operational improvements, and compliance with DoD security requirements while maintaining an active Secret clearance.

Leads data engineering and data science teams, setting strategy and delivering scalable pipelines, data architecture, models, analytics infrastructure, and data governance. Partners with product, analytics, and business stakeholders to prioritize initiatives, assess upstream changes, maintain data quality, and support Snowflake-based warehousing. This hands-on leadership role includes mentoring staff, contributing to technical codebases, and advancing data science and engineering solutions.

Develop and productionize machine learning models and predictive analytics using Python, Databricks, PySpark, SQL, and Delta Lake. Build scalable data science workflows, resolve healthcare data quality and entity-resolution issues, and apply Master Data Management practices. Partner with engineering, product, analytics, and business teams to deliver governed, HIPAA-compliant solutions. Perform exploratory analysis, feature engineering, model evaluation, deployment, documentation, and data lineage management for healthcare and member engagement initiatives.

Leads complex AI client projects from requirements gathering through delivery, serving as the primary client contact and coordinating Sales, Operations, Product, and Engineering. Responsibilities include defining scopes and delivery plans, managing risks, quality, timelines, budgets, profitability, and KPIs, resolving execution challenges, and improving scalable processes for AI project delivery.

Develops and positions Verizon Frontline technology solutions for public safety and public-sector clients. Partners with sales, business development, and cross-functional teams to identify digital transformation needs, create end-to-end solution roadmaps, lead customer engagements, and communicate value propositions through presentations, proposals, white papers, and industry events. Builds executive relationships, supports sales strategy, enables 5G and private-network use cases, and informs product roadmap priorities.

Lead technical customer engagements for strategic accounts, supporting sales, solution design, foundational implementations, and proof-of-value deployments. Discover requirements, map them to SailPoint solutions, educate customers on architecture and best practices, collaborate across sales, product, professional services, and customer success, and develop AI- and agentic-technology solutions for demonstrations and customer outcomes.

Forward Deployed Engineers support sales and customer engagements by discovering requirements, designing and implementing foundational SaaS solutions, delivering proof-of-value implementations, and educating customers on architecture and best practices. They collaborate with sales, product, professional services, and customer success teams; use AI and agentic technologies to solve customer problems; lead technical engagements; document requirements; and develop reusable demonstration solutions. The role may require up to 15% travel.

Leads a data science team focused on customer intelligence and personalization across digital products, apps, newsletters, and marketing channels. Develops lifetime value, segmentation, retention, recommendation, attribution, forecasting, and engagement models. Owns product funnel analytics and experimentation, including A/B testing and causal inference. Partners with Product, Marketing, Editorial, Data Operations, and Engineering to translate customer behavior into product improvements, measurable growth, and scalable data capabilities.

Analyze and characterize conversational audio data, identify underrepresented areas, and build active-learning and human-in-the-loop workflows. Develop representative benchmarks, automate model adaptation, and create reusable data analysis and scoring systems. Partner with research, engineering, and data teams to run experiments, improve models, organize data, and translate complex findings into measurable product improvements.

Leads the enterprise data strategy, builds and scales the Data & Analytics team, and oversees data warehouse modernization, migration, governance, KPI standardization, and data quality. Partners with executives and cross-functional teams to convert data into actionable insights, operational improvements, predictive analytics, and AI-enabled workflows. The role requires hands-on Python, SQL, cloud, machine learning, and ETL expertise, plus strong leadership and communication skills.

Develops, calibrates, validates, and maintains credit risk models, including PD, LGD, and EAD models, for lending, collections, loss forecasting, capital planning, and stress testing. Analyzes large datasets, evaluates model performance, documents model changes, supports systems testing, and communicates statistical insights to stakeholders and management. Collaborates across the credit union to improve risk-return strategies and reporting.

Leads complex enterprise SaaS delivery programs for major banks, owning governance, client and executive relationships, commercial controls, risk management, regulatory deadlines, third-party coordination, and successful go-live. The role requires deep financial crime compliance technology experience, including AML, KYC, transaction monitoring, sanctions screening, or case management platforms, plus proven Tier 1 bank implementations, program turnaround expertise, cloud delivery, and senior stakeholder credibility.

Lead independent validation and ongoing monitoring of complex financial and analytics models, including ALM, loss forecasting, loan transition, corporate finance, and engagement models. Identify weaknesses, communicate findings, guide remediation, and strengthen model governance. Collaborate with Finance, Quantitative Research, Growth Analytics, Internal Audit, Internal Controls, Accounting, and Compliance to maintain Affirm’s model risk framework and address audit, regulatory, and examiner requests.

Leads KeyBank’s Red Team and offensive security program, including adversary emulation, penetration testing, physical and application assessments, cloud security testing, AI security evaluations, and purple team exercises. Develops testing strategy, methodologies, tooling, metrics, and maturity roadmaps; mentors engineers; coordinates internal and third-party engagements; validates remediation and attack paths; and presents findings and strategic recommendations to executives and cybersecurity stakeholders.

Lead G2’s experimentation practice across products and digital marketplaces. Design experimentation standards, causal inference methods, metrics, guardrails, and analysis approaches; partner with product and engineering to implement experimentation platforms and instrumentation. Build models, design auctions, ship production systems, evaluate modern statistical methods, and address marketplace interference and low-traffic constraints. Mentor data scientists and evangelize rigorous data science practices across the organization.

Leads Tala’s Machine Learning Engineering team in building and operating platforms for model development, real-time inference, streaming features, batch processing, deployment, monitoring, and production reliability. Manages and develops 4–6 engineers, owns delivery and prioritization, provides architectural leadership, improves engineering practices and SLOs, and partners with Data Science, Data Engineering, Product, Credit, and Business Development teams.

Consult as a fractional data scientist for hedge funds, private equity firms, and family offices. Lead data science initiatives: build infrastructure, develop and deploy models, create portfolio dashboards, monitor post-deployment performance, and partner with investment teams to turn data into actionable investment insights. Advise on vendor selection, data quality, technology stacks, KPIs, and governance.

Lead positioning, messaging, go-to-market strategy, launches, channel enablement, competitive intelligence, and analyst relations for Sophos’ AI cybersecurity solutions. Translate complex technical capabilities into buyer- and partner-focused narratives, build launch assets and sales tools, and coordinate cross-functional execution across product, sales, marketing, and research teams. The role also develops customer feedback loops, competitive battlecards, and category-defining market perspectives.

Leads the development of partner enablement programs for Databricks and Snowflake ecosystems. Establishes strategies, governance, stakeholder relationships, learning pathways, workshops, bootcamps, champion networks, and readiness frameworks for technical and business audiences. Translates data, AI, analytics, and lakehouse use cases into scalable learning experiences, aligns programs with partnership growth objectives, measures engagement and effectiveness, and continuously improves initiatives based on partner feedback and business impact.