Top Senior 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.

Lead end-to-end data science projects, develop machine learning models, collaborate with stakeholders, mentor team members, and communicate insights effectively.

Develop, deploy, and monitor machine learning and analytic capabilities for defensive cyber operations. Ingest and transform multi-source data, build data pipelines, validate operational models, collaborate with analysts to deliver actionable insights, and document processes for reproducibility in high-security environments.

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.

GliaCell seeks a Data Scientist with experience in software development and strong communication skills. Responsibilities include data analysis, modeling, and working with government contracts. Must possess a TS/SCI clearance and programming expertise in Python and R.

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

Drive analytics and modeling to inform product strategy for Property & Casualty insurance. Build and productionize ML/statistical models, create visualizations and dashboards, manage exposure tools and regulatory reporting, and partner with Actuarial, Underwriting, Distribution, and Legal to execute product initiatives.

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.

Design, build, and deploy predictive GTM models (LTV, attribution, propensity). Lead experimentation and causal analyses, define KPI measurement frameworks, partner with Data Engineering, and translate statistical insights into actionable recommendations for Sales, Marketing, and Customer Success.

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

Develop and tune ML models, productionize and deploy strategies for ML systems, and align cross-functionally to communicate performance metrics.

Lead healthcare and pharmaceutical marketing analytics: analyze CRM, media, healthcare and behavioral data; build segmentation, attribution, audience scoring, and predictive models; develop measurement frameworks; use Python, SQL, BI and automation; translate insights for executives; mentor juniors and partner with Strategy, Media, and Client Services.

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.

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.

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.

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.

As a Data Scientist, you will build predictive models, develop software tools, and analyze geoscientific data to support mineral exploration and discovery.

As a Data Scientist, you will develop predictive models, analyze geoscientific data, and collaborate with geoscientists to improve mineral exploration efforts.

As a Staff Data Scientist, you will develop data-driven fraud prevention solutions using Generative AI, design scalable ML pipelines, and mentor junior data scientists while collaborating across teams to improve analytics and decision-making.

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.

As a Staff Data Scientist, you will lead initiatives to build and optimize machine learning models, collaborate across departments, and solve complex business problems using data.