Top Data Science Jobs in Baltimore, MD

Design and train LLMs and agentic systems for cybersecurity using RLHF/RLAIF and supervised fine-tuning. Build agent architectures, tooling, retrieval/memory, and evaluation pipelines with rigorous statistical benchmarking. Optimize prompts and inference, collaborate with engineers to productionize prototypes, and drive research on agent planning, safety, and reliability.

This role involves applying advanced data science and machine learning methods to healthcare data, leading teams, managing client relations, and developing analytics products for payers, while mentoring junior staff.

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.

Build and deploy statistical and machine learning models for the Toast platform. Collaborate with product, engineering, and business teams to identify opportunities, develop data-driven solutions, evaluate models, and communicate insights to stakeholders. Work in a fast-paced environment and contribute to production ML systems and experimentation.

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 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 Data Scientist at SentiLink, you'll develop fraud detection models using machine learning, engage in product development, and support analysis across teams. This role emphasizes hands-on technical work and end-to-end project ownership in a fast-paced environment.

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.

Perform data exploration, cleaning, analysis, and visualization; develop predictive models and algorithms using ML/AI/NLP techniques; collaborate with clients to translate data into actionable insights and deploy analytical solutions.

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 and ML techniques to national security problems: curate, transform, analyze large SIGINT/RF/PROFORMA datasets; build reproducible analytics, models, and visualizations; automate workflows and optimize data pipelines; communicate results to technical and non-technical 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 2 role involves expertise in AI/ML, proficiency in Python, and contributions to data processing, modeling, and analysis to derive meaningful insights from large datasets.

This role involves developing NLP solutions for language data, evaluating models, and enhancing data processing capabilities in a national security context.

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

Lead design and evolution of large-scale nodal power market models. Define mathematical approaches, develop optimization/forecasting methodologies (MILP, SCUC/SCED), collaborate with engineers to productionize models, work with product and customers to translate market problems into software, mentor data scientists, and guide long-term product strategy.

Apply data science and geospatial analysis at national scale: process, validate and analyse complex urban datasets; develop scripts, tools and notebooks; build reproducible, versioned analytical workflows; collaborate in cross-functional squads; produce documentation and handover materials to enable reuse and scalable delivery.

As a Senior Data Scientist, you will lead high-complexity projects, develop ML and NLP solutions, and collaborate across teams to drive business impact through statistical modeling and data analysis.

As a Data Scientist, you will analyze data to provide insights, develop algorithms, and solve complex problems using machine learning and scientific methods.

Data Scientist role focused on leveraging IoT, machine learning, and AI to analyze complex datasets for actionable insights across various sectors.

The data scientist will analyze complex datasets using statistical methods, develop algorithms, and provide data-driven insights to support client decision-making.

The role involves evaluating IT security data, documenting security gaps, developing interoperability measures, prototyping algorithms, and generating analytical reports. Strong network engineering knowledge and TS/SCI clearance are required.