Top Senior Data Science Jobs

Leads data science and advanced analytics initiatives for PNC’s Home Lending organization. Directs data gathering, processing, mining, modeling, and production AI solution delivery using structured and unstructured data. Designs agentic LLM workflows, propensity models, and large-scale backtesting while promoting responsible AI, prompt governance, and model validation. Provides technical leadership to data science teams and partners with architects, analysts, engineers, and visualization experts to deliver actionable business insights.

Develop machine learning models for business card credit underwriting across the full lifecycle, from design and training through validation and implementation. Collaborate with data scientists, engineers, product managers, and business stakeholders to develop scalable solutions using large datasets and cloud technologies. Translate complex analysis into business outcomes and apply statistical methods including classification, clustering, sentiment analysis, time series, and deep learning.

Develop machine learning and statistical models across the full lifecycle, analyze large numeric and textual datasets, and deliver data-driven solutions for small-business marketing, deposits, customer engagement, retention, and experience. The role partners with data scientists, engineers, and product managers while using Python, cloud platforms, distributed computing, and emerging AI technologies.

Develop machine learning and statistical models for consumer risk using large-scale financial data. Responsibilities include partnering with data scientists, engineers, and product managers; analyzing numeric and textual datasets; building, validating, backtesting, and implementing models; researching emerging technologies; and translating technical findings into business outcomes. The role requires strong statistical knowledge, data retrieval and analysis skills, and proficiency with cloud and open-source technologies.

Develop machine learning and statistical models using large-scale structured and textual data to support Small Business Bank marketing and deposit strategy. Partner with software engineers, product managers, and data scientists to deliver data-driven products. Build account-level lifetime value and NPV models, translate technical findings into business outcomes, and manage model development from design through implementation.

Develop and deploy scalable optimization, simulation, and machine learning models for banking decision systems. Translate complex business challenges into mathematical problems, build production-grade algorithms using Python and optimization solvers, design experiments, and integrate modeling solutions with software systems. Collaborate with Product, Engineering, and Business teams to improve customer experiences, risk policies, and operational decision-making.

Lead end-to-end data science initiatives for economic and financial analysis. Responsibilities include curating complex datasets, developing statistical, machine learning, econometric, and generative AI solutions, validating data sources, identifying economic trends, generating forecasts, and communicating insights to technical and executive audiences. The role partners with economists, strategists, product owners, and data scientists while advancing LLM and GenAI adoption.

Designs enterprise technical solutions spanning applications, integrations, data, infrastructure, and cloud platforms. Leads technical stakeholders and implementation teams while resolving risks. Defines data requirements, collection methods, and quality standards; builds systems for analysis and insight generation; improves models and algorithms; and ensures security, privacy, and compliance. The role also applies NLP, generative AI, and large language models to scalable, knowledge-driven solutions.

Leads the full analytics lifecycle for advertising sales, including data preparation, exploratory analysis, predictive modeling, validation, productionalization, interpretation, and recommendations. Develops scalable data-driven solutions using statistical and machine learning methods, presents findings to varied audiences, mentors junior staff, contributes to strategic direction, and manages project execution. Requires advanced programming, SQL, cloud, big-data, forecasting, optimization, and AI/ML expertise.

Leads the full analytics lifecycle for Spectrum Reach’s advertising sales business, including data preparation, exploratory analysis, predictive modeling, validation, productionization, forecasting, and interpretation. Develops scalable analytics products, synthesizes recommendations, presents findings to diverse audiences, manages project execution, and mentors junior data professionals. Requires advanced statistical, machine learning, programming, cloud, and big-data expertise.

Leads Responsible AI data science initiatives by developing and validating AI testing protocols, automating analyses with Python, identifying PII and PHI vulnerabilities, and designing red-team scenarios for conversational AI. The role documents responsible AI practices, supports governance and regulatory compliance, communicates findings to legal, compliance, and technical stakeholders, and mentors colleagues. It requires expertise across traditional machine learning, generative AI, agentic techniques, AI ethics, fairness, and the full AI lifecycle.

Develop and productionize AI, machine learning, and statistical models for workforce demand forecasting, capacity optimization, scheduling, and real-time decision-making. Responsibilities include framing ambiguous business problems, selecting theoretically grounded modeling approaches, collaborating with stakeholders, ensuring solution robustness, communicating data-driven recommendations, and supporting complex cross-functional projects. Advanced work may involve time series, operations research, NLP, neural networks, and cloud technologies.

Conduct applied AI research and develop automation, knowledge management, semantic search, retrieval, and reasoning systems. Build and evaluate proof-of-concepts, create frameworks for assessing AI risks and business impact, and collaborate with engineering teams to productionize successful concepts. The role explores agentic, causal, explainable, neuro-symbolic, and knowledge-enhanced AI, while contributing to publications and patents across financial services, fraud, risk, insurance, and marketing applications.

Leads end-to-end data science initiatives involving machine learning, statistical modeling, causal inference, sequence analysis, and scalable insight generation. Builds and deploys production-ready solutions using Python, SQL, Spark, Databricks, and cloud platforms. Provides technical leadership and mentorship, establishes model validation and governance practices, manages cross-functional initiatives, and communicates analytical findings to technical and business stakeholders. The role supports agricultural and digital product applications.

Develop and operationalize advanced analytics for a large-scale government data platform. Responsibilities include statistical modeling, machine learning, predictive analytics, data exploration, model validation, experiment design, and integrating analytical capabilities into production workflows. The role collaborates with engineers, analysts, and government stakeholders to translate mission requirements into scalable solutions and communicate findings to technical and executive audiences.

Develop and operationalize statistical models, machine learning algorithms, and predictive analytics for a large-scale government data platform. Analyze complex datasets, identify patterns and anomalies, validate models, and integrate analytical capabilities into production workflows. Collaborate with engineers, developers, analysts, and government stakeholders to translate mission needs into scalable solutions and communicate findings to technical and senior audiences. The role requires an active TS/SCI clearance and is primarily onsite in Herndon, Virginia, or Westminster, Colorado.

Develop product analytics and data science solutions for small-business insurance and banking products. Apply statistical analysis, predictive modeling, experimentation, AI, and customer journey analytics to improve product performance, engagement, lead generation, and client outcomes. Establish KPI and measurement frameworks, analyze data using Python and SQL, communicate insights to senior stakeholders, and identify scalable AI and agentic use cases in a regulated environment.

Leads complex data science and AI initiatives, developing and deploying machine-learning solutions centered on LLMs, agentic workflows, and RAG systems. Translates stakeholder needs into technical roadmaps, mentors analysts and data scientists, manages project budgets and schedules, ensures quality, and designs reliable AI applications using embeddings, vector databases, retrieval systems, and AI workflow platforms.

Develops data integration workflows, dashboards, statistical and predictive models for biotherapeutics process development. Analyzes complex scientific and process datasets, identifies trends and anomalies, supports process improvement, and communicates findings to technical teams. The role also troubleshoots data and software issues, trains team members, collaborates externally, and contributes to project deliverables and modeling initiatives.

Develop machine learning and statistical models for Business Cards marketing, including design, training, evaluation, validation, and implementation. Analyze large numeric and textual datasets using Python, cloud computing, and big-data technologies. Partner with data scientists, engineers, product managers, analysts, and marketers to translate insights into personalized campaigns and measurable business outcomes.

Develops data science and machine learning solutions for auto finance products. Analyzes digital customer behavior, builds predictive models, evaluates A/B experiments, and creates measurement frameworks and KPIs to improve conversion and engagement. Partners with Product, Technology, Design, Risk, and business leaders to translate complex questions into actionable insights, communicate recommendations, and support strategic decisions. May also build conversational AI solutions and integrate machine learning services into applications.

Develops data-driven insights for Business Banking deposit and cash management products. Partners with product managers to translate business questions into analyses, forecasting, diagnostic deep dives, and performance reporting. Communicates findings to nontechnical stakeholders, supports product strategy and customer engagement, and maintains strong data quality and controls. The role requires advanced SQL, experience across on-premises and cloud databases, and use of large language models to improve code development.

Lead claims-based studies and actuarial modeling to quantify Nourish’s impact on healthcare spending, utilization, total cost of care, PMPM savings, and ROI. Apply causal inference, risk adjustment, and matched comparison methods to evaluate care programs. Translate findings into reports and executive narratives for health plan partners while building reusable datasets and analytical workflows with Analytics Engineering.

Leads data science initiatives for financial services pricing by partnering with engineers and product managers, analyzing large-scale data, and developing machine learning models from design through implementation. Responsibilities include statistical modeling, validation, backtesting, translating technical findings into business outcomes, evaluating emerging technologies, and developing team talent.

Analyzes structured and unstructured datasets; develops algorithms, dashboards, queries, and statistical models; transforms and mines data; applies mathematics, statistics, operational mathematics, and machine learning; interprets data and prepares predictions; and collaborates with business units to drive solutions. The role requires 6–9 years of experience with a bachelor’s degree or 4–7 years with a master’s degree, plus CUI and OPSEC certification eligibility.