Top Senior Data Science Jobs in Baltimore, MD

Lead research and engineering of production-grade LLM/GenAI systems for cybersecurity: design models and architectures, drive data labeling and evaluation, collaborate with product and engineering to deploy scalable solutions, mentor data scientists, set technical strategy, and advance AI safety, red-teaming, and applied ML innovations for detection and operational use.

Lead advanced analytics and ML efforts to extract insights from large-scale historical data, design features and data representations for models and LLM/agentic systems, partner with product and engineering to build data pipelines and prototypes, evaluate AI workflows, and drive innovation through experiments and empirical analysis to inform product strategy.

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 efforts by designing and evaluating experiments, building dashboards, and producing statistical insights. Partner with product, design, and engineering to measure product success, identify optimization opportunities, and embed ML-driven personalization into the product.

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.

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.

Lead complex modeling projects combining deep learning, LLMs, and traditional techniques. Prototype, deploy, and monitor production models, mentor data scientists, collaborate with engineering/product, and translate results into business impact for insurance customers.

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 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.

Design, implement, and deploy AI/ML solutions and autonomous agents using LLMs, reinforcement learning, and agentic AI. Optimize and scale neural models, apply prompt engineering and RAG, document results, follow software development best practices, and collaborate with mission teams to support operational objectives.

Apply statistical and computational techniques to large complex datasets to develop, evaluate, and deploy analytical models and reproducible workflows. Clean, transform, and visualize data, communicate findings to technical and non-technical stakeholders, and translate mission requirements into operational data solutions.

Design, implement, and deploy AI/ML solutions (including LLMs and autonomous agents) to analyze large, complex CNO datasets, develop scalable analytical methods, derive mission insights, and collaborate with technical and mission teams while documenting methods and results.

Work with large-scale datasets and distributed environments to build scalable data-processing workflows and automated pipelines using Python and Spark. Apply network and protocol analysis to communications data, transform and integrate multiple data sources, document methods, and collaborate with technical and mission teams to deliver analytic solutions supporting mission requirements.

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.

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.

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.

Lead evaluation and data strategy for advanced AI, vision, and perception systems. Define metrics, build evaluation frameworks, audit artifacts, prioritize fixes, and translate model behavior into product decisions and data-improvement loops to ensure production readiness and downstream usefulness.

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 development and deployment of large-scale LLM and GenAI solutions for cybersecurity. Drive research strategy, model training, evaluation, safety/red-teaming, and cross-functional productization. Mentor data scientists, set technical standards, and represent the team through publications and thought leadership.

Lead research and experimentation to measure ad campaign performance and effectiveness. Design evaluation frameworks, build measurement solutions, develop models for lift, conversion, and attribution, run experiments and analyses, partner with product/engineering/design/sales, present insights, mentor teammates, and foster technical community and culture.

Lead design and execution of scalable experimentation frameworks for Netflix Ads. Develop auction-based, biddable media models, solve cold-start measurement problems globally, apply causal inference and ML, partner with product and engineering, and translate analytic results into strategic recommendations to optimize marketplace dynamics and member experience.

Lead design, execution, and interpretation of A/B tests and quasi-experiments; apply causal inference methods; partner with product, engineering, and marketing; mentor data scientists; build experimentation frameworks; extract and analyze data using SQL and Python; communicate results to stakeholders.

The Data Scientist will apply machine learning and statistical analysis to support mission analysis, develop analytical tools, and visualize complex datasets for insights.