Top Data Science Jobs in Baltimore, MD

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.

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.

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 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.

Entefy seeks a Senior Data Scientist with a Master's or PhD in a relevant field, and 3+ years of experience. Responsibilities include delivering advanced analytics, leading teams, and extracting insights from datasets.

Design and implement analytic methods to extract meaning from large, messy NSA/CSS datasets. Build and evaluate models, manage and curate data, translate mission needs into technical requirements, and communicate technical conclusions to non-technical stakeholders while accounting for collection and processing constraints.

The Senior Data Scientist will design and implement machine learning solutions, conduct advanced statistical analyses, and manage data-related tasks, requiring a high level of expertise.

The position involves unlocking insights from data sets using IoT and AI, developing algorithms, and collaborating with clients to solve data-driven problems.

Design and apply statistical, mathematical, and computational methods to extract value from large, messy datasets. Build, evaluate, and communicate analytic and ML models, translate mission needs into technical requirements, and recommend solutions while explaining results to non-technical stakeholders.

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

The Data Scientist will develop advanced NLP solutions, evaluate model performance, and collaborate on production system integrations for language data processing.

The Data Scientist will develop data-driven solutions, integrate APIs, manipulate data using Python, analyze large datasets, and collaborate with teams.

The Data Scientist will design and develop NLP and NER models, validate ML models, and ensure compliance for AI solutions, focusing on unstructured data processing.

Perform data science on government datasets: extract VPN info, apply DX/XKS and CASN knowledge, build models, curate and analyze large datasets, translate mission needs into technical requirements, and communicate findings to non-technical stakeholders.

Develop and sustain analytics tools using Python and customer toolset. Apply mathematical, statistical, and computational methods to large, messy national agency datasets, build and validate models, translate mission needs into technical requirements, and communicate complex results to non-technical audiences.

Perform data and computer science analysis to support customer operations using advanced machine learning, statistical methods, and programming (Python, Java, C/C++). Curate and process large, messy national agency datasets, build models and inferences, translate mission requirements into technical solutions, and communicate results across teams. TS/SCI with polygraph clearance required.

The Data Scientist Level 4 develops strategies to extract insights from large datasets, utilizing advanced analytics and machine learning techniques. Responsibilities include statistical analysis, modeling, and effectively communicating findings to non-technical audiences.