Top Principal Data Scientist Jobs in Boston, MA

Defines UKG’s company-wide data science and AI strategy, architects enterprise-scale systems, guides infrastructure investments, and leads agentic AI governance. Influences executives, drives business-critical ML initiatives, establishes standards for MLOps, model governance, data quality, and responsible AI, and represents the organization externally. Builds leadership capability through mentoring, hiring strategy, career frameworks, and learning programs while evaluating emerging technologies, vendor relationships, and competitive opportunities.

Lead end-to-end data science for customer-embedded, production solutions: acquire and prepare messy datasets, develop and evaluate models tied to business outcomes, run experiments, deploy operational models at scale, coach cross-disciplinary teams, and drive strategy, ethics, and privacy discussions.

Leads the design, development, deployment, and scaling of production AI/ML solutions across NLP, speech analytics, conversational AI, and generative AI. Provides technical leadership through mentoring, architecture decisions, code reviews, and engineering standards. Builds MLOps and RAG pipelines using cloud and open-source technologies, optimizes GPU workloads, works with streaming data, and partners with business, product, and engineering teams to deliver measurable value.

Provides technical leadership for data science, engineering, and software teams developing machine learning applications for manufacturing and process industries. Develops AI, modeling, simulation, and cognitive computing solutions; evaluates emerging technologies; collaborates with customers and product teams; and represents the company at industry and academic events. Requires strong expertise in mathematics, statistics, optimization, machine learning, and software development, with a focus on delivering research-driven customer value.

Develop and deploy protein machine learning models predicting immunogenicity, stability, and manufacturability for vaccine design. Apply protein language models and foundational AI to analyze sequence, structure, and functional data. Collaborate with structural biology, protein design, and laboratory teams, maintain reproducible modeling code, communicate scientific findings, and mentor colleagues in protein modeling.

Leads development and deployment of statistical, machine learning, and causal inference models for customer decisioning. Designs experiments, estimates treatment effects and incremental value, evaluates targeting performance, and integrates analytical solutions into governed production systems. Partners with business and technology teams, communicates complex findings, and continuously improves models using experimental and operational results.

Develops data quality checks, metadata standards, and AI use-case inventories for HHS. Cleans and integrates complex datasets, applies machine learning and NLP for automated tagging and classification, evaluates AI governance risks, and produces reporting datasets, dashboards, and recommendations. The role requires translating ambiguous federal policy and reporting requirements into repeatable analytical workflows while collaborating with product, design, engineering, and government stakeholders.

Build and maintain Marketing Mix Models to measure marketing effectiveness, develop attribution metrics, and create optimization solutions for budget allocation and scenario planning. The role applies statistical, Bayesian, time series, regression, and optimization methods using Python and SQL. It partners with marketing and cross-functional teams to translate analytical findings into actionable business recommendations and influence investment decisions.

Set the technical vision for data science, lead complex statistical and machine learning model development from concept through production, and architect scalable modeling platforms and pipelines. Develop credit risk, pricing, and loss forecasting models; establish model governance standards; partner with senior leaders; mentor data scientists; and communicate technical strategy to executives. The role emphasizes production deployment, monitoring, cloud architecture, and high-impact decision-making across the business.

Leads data science, AI, digital health, and analytics strategy for Immunology R&D. Partners with scientific, clinical, platform, and engineering teams to identify use cases, analyze workflows, evaluate emerging technologies, develop scalable solutions, and improve research execution and decision-making. The role focuses on healthcare, imaging, clinical, biomarker, real-world, and digital health data, including generative and agentic AI applications.

Leads the data science platform and machine learning strategy, building data marts, predictive models, MLOps infrastructure, and analytics capabilities. Analyzes healthcare claims, clinical, workflow, and operational data to risk-stratify patients, assess clinical program impact, support dashboards, and improve patient and provider engagement. Collaborates with clinical, operations, finance, product, executive, and technology teams while serving as a trusted analytics expert for a business workstream.

Lead end-to-end AI/ML initiatives to improve student retention, engagement, and enrollment. Architect and operate data pipelines, feature stores, and production ML systems; deploy, monitor, and automate models; run experimentation programing and measure business outcomes. Mentor team members and set technical standards across Product, Engineering, and CX.

The Senior Data Engineer will transform real-world data into analytics-ready datasets, build scalable pipelines, and conduct analyses to support scientific and business decisions, collaborating closely with data science teams.

Leads consumer personalization strategy and production development for recommendations, ranking, search, browse, carts, marketing, and agentic AI experiences. Builds recommender systems, learning-to-rank models, LLM agents, evaluation frameworks, and experimentation programs. Partners with Product and Engineering on deployment, monitoring, and model quality while mentoring senior data scientists, setting technical direction, shaping roadmaps, and communicating trade-offs to executives.

Lead development and deployment of machine learning models across the credit card lifecycle. Partner with cross-functional teams to build data-driven products, analyze large numeric and textual datasets, validate and implement models, and translate technical insights into business impact.

Design, build, validate, and deploy machine learning models across the credit card lifecycle. Partner with cross-functional teams, analyze large numeric and textual datasets using Python, Spark, H2O and cloud platforms, and translate technical insights into business impact for card products.

Build and validate production-grade ML and AI systems across pricing, underwriting, claims, and portfolio management. Work with structured and unstructured data, LLMs and agentic workflows, extract information from documents, resolve entities, create feature pipelines and inference services, quantify uncertainty, monitor drift, and measure business impact in collaboration with engineers, actuaries, underwriters, and product teams.

Leads the design, development, deployment, and monitoring of advanced statistical and machine learning models for insurance pricing, underwriting, claims, fraud, retention, and growth. Advises executives and actuarial teams, establishes modeling and experimentation standards, ensures responsible and scalable productionization, and mentors data scientists. The role also advances MLOps, AI infrastructure, model lifecycle management, explainability, fairness, and data science strategy.

Lead generative AI initiatives: define 18-24 month roadmap, develop and deploy LLMs and multimodal models for document and 3D data extraction, architect Siemens integration, drive data/ML ops, mentor scientists, and align cross-functional teams to deliver production-grade AI solutions.

Lead design and ownership of ZoomInfo's PLG measurement system, define KPIs and leading indicators, analyze end-to-end customer journeys, diagnose growth issues, and influence product investments. Build AI-native, automated analytics workflows, reporting, and monitoring while partnering cross-functionally to prioritize experiments and scale insights that drive adoption, retention, monetization, and expansion.

The Senior Data Scientist will lead innovative data science efforts, leveraging advanced analytics, visualization, and insights from complex datasets to boost productivity.

Entefy seeks a Senior Data Scientist with a Master's or PhD in a relevant field, and 3+ years of experience. Responsibilities include delivering advanced analytics, leading teams, and extracting insights from datasets.