Top Senior Data Science Jobs in Baltimore, MD

Lead teams applying advanced data science and machine learning to large-scale claims, clinical, and member data to generate actionable insights that reduce cost of care and improve population health. Manage client relationships, mentor staff, ensure project delivery and quality, develop payer-focused analytics products, present findings to senior stakeholders, and promote continuous improvement and knowledge sharing.

Lead end-to-end pricing experimentation and strategy for consumer and business products. Design and analyze A/B tests, build pricing models and production-grade data pipelines, partner cross-functionally, and present actionable recommendations to senior leadership.

Lead design and delivery of scalable ML systems across the full lifecycle for recommendations, demand forecasting, targeting, and personalization. Collaborate with engineers, product, and stakeholders to set architecture, metrics, and production best practices; mentor data scientists; lead experimentation and deploy/monitor models using cloud and MLOps tooling.

As a Staff Data Scientist at SentiLink, you will develop fraud detection models, conduct analyses, collaborate across teams, and drive the development of financial risk products.

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.

As a Data Scientist Level 3, you will apply data science expertise to national security challenges, develop analytical tools, and communicate insights effectively to diverse audiences.

As a Data Scientist, Level 3, you'll leverage Python to automate workflows, perform data manipulation, and create visualizations, applying advanced analytics to complex datasets and communicating insights to varied audiences.

As a Senior Data Scientist, you'll develop fraud detection models, perform detailed analyses, and work closely with teams to drive product innovation and business outcomes.

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

Lead technical design and implementation of large data and software solutions, define architecture and standards, mentor developers, consult with customers on feasibility and requirements, integrate emerging technologies, deliver product demonstrations, and support end-to-end projects—applying machine learning and defensive cyber operations expertise in secure environments.

The Senior Data Scientist will develop data pipelines for AI applications, optimize data structures, manage databases, and ensure data quality and security.

Develop and deploy machine learning and statistical models to support defensive cyber operations. Curate and integrate diverse data sources, automate anomaly detection, evaluate model performance, and collaborate with analysts and developers to operationalize analytics for USCYBERCOM.

Develop and deploy machine learning and statistical models to support defensive cyber operations for USCYBERCOM. Curate and integrate diverse data sources, prototype analytic capabilities, monitor model performance, and collaborate with analysts and developers to productionize solutions. Document processes and maintain configuration management for datasets.

Provide defensive cyber operations support to USCYBERCOM by developing ML and statistical models, curating diverse data sources, deploying models to production, collaborating with analysts and developers, documenting processes, and researching data science tradecraft.

Perform network exploitation and offensive cyber operations, build rapid analytic methodologies and tools, analyze adversary tactics, develop data visualizations, automate analytics with developers, conduct gap analysis, and advise on comprehensive data strategy to support intelligence missions.

Support national security operations by applying machine learning, statistical analysis, and scalable data processing to large datasets. Build automated pipelines, curate and transform data, develop and refine analytical algorithms and models, create visualizations and dashboards, and translate mission requirements into reproducible analytics to inform stakeholders.

Apply advanced data science, machine learning, and statistical techniques to large-scale cyber and network datasets. Build data pipelines, curate and normalize data, develop and refine analytical models (including NLP/LLMs), create visualizations and automated workflows, and translate mission requirements into actionable analytics to support national security operations.

The Data Scientist will develop advanced analytics for cybersecurity, collaborate with engineers and analysts, model complex data, and support threat intelligence.

Provide analytics and data-driven insights for CoverMyMeds clients, prioritize work that drives commercial outcomes, build relationships with account teams, apply statistical and predictive methods, monitor portfolio health, deliver client-facing visuals and recommendations, support complex requests and escalations, and inform strategic decisions across product, analytics, and operations.

Lead and deliver end-to-end data science projects: design, build, deploy, and monitor ML/statistical models for credit risk, pricing, collections, and fraud. Partner with cross-functional teams to integrate models into production, set model development standards, mentor engineers, and maintain reliable ML pipelines and monitoring systems.

Own analysis and algorithmic solutions for ads delivery; train, deploy, and scale ML/optimization models into production; build logging, monitoring, and lineage; improve data pipelines; mentor data scientists; use agentic AI tools daily; collaborate with engineers to integrate models into ads systems and handle on-call production incidents.

Develop frameworks and tooling to estimate long-term impacts of product changes from short-term experiment outcomes. Build causal inference methods (experimental, econometric, quasi-experimental), evaluate heterogeneous treatment effects, own major estimation problems, and communicate results to technical and non-technical stakeholders to drive better long-term decisions.

Design, develop, and evaluate conversational AI agents and generative AI products. Collaborate with AI scientists, ML engineers, and Responsible AI/Model Validation teams to ensure state-of-the-art, ethical solutions and support deployment and integration of conversational systems.

The Sr. Football Data Scientist will build, deploy, and refine analytical models for football insights, managing large datasets and collaborating with teams for high-quality analytics solutions.

Lead analytical efforts in Real World Data research, develop specifications and methodologies, manage projects, and communicate findings to stakeholders.