Top Senior Data Science Jobs

Leads data science and machine learning initiatives addressing cybersecurity and technology risk. Responsibilities include analyzing security datasets, developing and evaluating statistical and deep learning models, engineering features, preparing production code, supporting model governance, and establishing controls for AI-assisted workflows. The role partners with cybersecurity, engineering, data, and business stakeholders while ensuring solutions are secure, auditable, interpretable, resilient, and aligned with regulatory expectations.

Develops end-to-end data science and generative AI solutions for payments and merchant services. Responsibilities include designing prompts, building chat assistants and workflow automations, creating Python and SQL data pipelines and Tableau dashboards, testing and monitoring AI models, developing algorithms and data models, and delivering customer insights and analytics. The role collaborates with business stakeholders and data teams to improve decision-making, automate processes, and support commercial growth.

Leads cybersecurity data science initiatives, including exploratory analysis, statistical modeling, machine learning, deep learning, feature engineering, model governance, and secure production coding. Partners with cybersecurity, engineering, and business stakeholders to define use cases, deploy reliable models, validate AI-assisted recommendations, establish AI workflow guardrails, and address security, resiliency, auditability, and regulatory requirements.

Build enterprise Generative AI solutions for Commercial Banking using multi-agent systems, advanced RAG, context engineering, tool-calling frameworks, and machine learning. Partner with data scientists, ML engineers, and product managers to develop, evaluate, validate, fine-tune, and deploy AI pipelines over large numeric and textual datasets. Translate complex technical work into business outcomes while researching emerging AI methods.

Leads a US Card data science team developing machine learning solutions for customer behavior prediction and valuation forecasting. Partners with data scientists, engineers, product managers, and business stakeholders; builds models through design, training, validation, evaluation, and implementation; analyzes large-scale numeric and textual data; translates technical findings into business outcomes; and develops team talent.

Lead development of large-scale recommender and personalization systems using transformers, LLMs, reinforcement learning, sequence modeling, and multimodal learning. Build and evaluate foundation models and low-latency production systems using customer interaction data. Collaborate with engineering and product teams, translate research into practical applications, and support innovation in generative recommendations, conversational systems, and cross-domain personalization while developing team talent.

Develop enterprise Generative AI solutions for Commercial Banking using multi-agent systems, advanced RAG, context engineering, and tool-calling frameworks. Partner with data scientists, machine learning engineers, and product managers to build, evaluate, validate, fine-tune, and deploy AI pipelines across numeric and textual data. Apply statistical modeling, machine learning, deep learning, NLP, information retrieval, and cloud technologies while translating complex technical work into business outcomes.

Leads enterprise AI solution validation and certification, making risk-based release decisions and overseeing post-deployment performance, risk, and safety monitoring. Partners with solution owners and data teams to enforce AI governance requirements, manage remediation, and provide authoritative guidance on validation standards. Directs advanced analytics, data mining, and machine learning initiatives while providing enterprise-wide program leadership and executive-level influence.

Leads payer healthcare data science and operations consulting initiatives, using business analytics to improve payer processes and performance. Manages teams, client relationships, project resources, strategic planning, process optimization, quality standards, and operational transformation. Coaches junior staff, promotes innovative technologies, and identifies opportunities to enhance operational excellence and business outcomes.

Senior Data Scientist partnering with Product, Engineering, Design, Operations, and Clinical teams to define metrics, design experiments, apply causal inference, analyze funnels and cohorts, and build predictive models. The role translates complex data into actionable product and business recommendations, operationalizes validated insights, and establishes standards for experimentation and analytical quality across patient, payer, outcomes, and provider-focused teams.

Develop and deploy machine learning solutions for enterprise risk and anti-money-laundering innovation. Partner with data scientists, engineers, and product managers to build models using structured and textual data, including NLP, graph modeling, deep learning, and Generative AI. Lead projects through design, training, validation, evaluation, and implementation while translating technical findings into business outcomes.

Build and scale AI-driven analytics and decision-support products for Finance. Responsibilities include prototyping LLM agents, multi-agent workflows, RAG, forecasting, evaluation harnesses, guardrails, data architectures, semantic layers, observability, and data governance. The role also owns AI and data roadmaps, experimentation frameworks, and business-impact measurement while partnering with Finance, engineering, and platform teams.

Leads fraud-risk analytics and strategy across the account lifecycle, analyzing fraud trends, account quality, performance metrics, profitability drivers, and operational processes. Directs complex projects from analysis through implementation and monitoring, identifies fraud risk drivers, and delivers recommendations to senior leadership. Collaborates cross-functionally, builds consensus, and communicates quantitative insights to executives and stakeholders using statistical methods, SAS, SQL, and spreadsheet tools.

Build data products and automations by translating business questions into technical requirements, assessing data and process gaps, and developing analytics solutions. Create actionable Power BI dashboards, support cross-functional decision-making, and guide junior data scientists and citizen developers. The role requires strong skills in Python, SQL, data analytics, AI, automation, data modeling, business requirements analysis, communication, and project management.

Develop and deploy machine learning and data science solutions for healthcare payment integrity. Responsibilities include data preparation, feature engineering, model development, evaluation, deployment, monitoring, LLM and NLP application, distributed data processing, and collaboration with engineering, product, and business teams. The role requires communicating insights, evaluating emerging AI technologies, and delivering scalable solutions that improve claims payment accuracy.

Lead complex data science and AI initiatives focused on healthcare affordability, medical cost management, and operational efficiency. Develop and deploy machine learning, causal inference, optimization, and AI solutions using healthcare claims and enterprise data. Guide architecture, governance, validation, and measurement of production models; mentor data scientists; establish technical direction; and communicate insights and business value to actuarial, clinical, business, technology, and executive stakeholders.

Lead the design, development, and operation of scalable data pipelines, trusted data products, metrics, and feature-ready datasets. Establish data quality, governance, orchestration, testing, observability, and engineering standards using Python, PySpark, SQL, dbt, Airflow, and Databricks. Partner with analytics, product, and engineering teams to support AI adoption and productivity measurement, while mentoring a team of two and driving delivery through ambiguous, cross-functional initiatives.

Partner with product owners to translate business problems into scalable data science, ML, AI, and GenAI solutions. Develop predictive, forecasting, optimization, and simulation models; analyze large datasets; build dashboards; deploy models in cloud environments; and contribute to data governance and infrastructure improvements.

Leads consumer data science strategy and high-impact analytical initiatives, including experimentation, causal inference, measurement frameworks, and AI-assisted analytics. Partners with Product, Engineering, and executives to shape roadmaps, define metrics, communicate recommendations, and prioritize business opportunities. Mentors data scientists, establishes technical standards, and develops scalable self-service analytics capabilities using modern data and AI tools.

Leads advanced data science projects involving machine learning, deep learning, statistical modeling, forecasting, segmentation, search, recommendations, ranking, and generative AI. Develops production-grade code and evaluation frameworks, deploys scalable models, collaborates with business and technical teams, communicates insights, and mentors junior data scientists.

Lead AI/ML data science projects for payment integrity, from stakeholder requirements through production deployment. Develop, evaluate, monitor, and refine machine learning models that detect payment issues and prioritize clinical audit inventories. Collaborate with engineering, infrastructure, operations, and business teams; communicate methodologies and insights to technical and non-technical audiences; and ensure compliance with ethical, legal, regulatory, and organizational standards.

Own analytical integrity for a payments observability and AI platform. Responsibilities include analyzing transactional data, validating metrics and model behavior, back-testing anomaly detection and forecasting models, monitoring data and model drift, triaging analytical defects, creating executive-ready visualizations, and partnering with product and engineering teams on requirements and prioritization.

Own product analytics for a healthcare platform by translating business questions into research plans, uncovering insights, modeling feature impacts, defining success criteria, and leading A/B testing. Partner with Product, Data Engineering, Finance, Clinical, and Operations teams to influence roadmap decisions, improve provider experience and quality, and optimize marketplace performance.

Lead analytics and applied AI initiatives using statistical and machine learning methods to solve business challenges and support sales and services growth. Partner with stakeholders to develop insights, models, and scalable digital solutions; mentor data scientists; research emerging techniques; and communicate findings to technical and non-technical audiences.

Lead advanced digital and rental analytics using GA4, BigQuery, Python, and SQL. Analyze clickstream data, customer journeys, conversion funnels, attribution, and site performance to improve revenue and customer growth. Define KPIs, develop analytics roadmaps, apply statistical and machine learning methods, establish data governance, and translate insights into recommendations. Collaborate with senior leaders, product owners, strategy teams, and technical stakeholders while supporting scalable measurement solutions and data-driven product development.