Top Data Science Jobs in Baltimore, MD

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 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 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.

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.

Lead design and implementation of data architecture, pipelines, and predictive models. Build and maintain ETL workflows, produce Tableau/Power BI dashboards, collaborate with stakeholders and executive leadership, document procedures, and support cross-team analytics efforts in an Agile environment.

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.

As a Data Scientist, you'll analyze and interpret complex data sets, develop algorithms, and work with clients to provide actionable insights, utilizing tools from machine learning and AI.

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.

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.

Develop and maintain Python-based tools and APIs to retrieve, process, aggregate, and analyze complex mission datasets. Apply AI/ML to optimize workflows, automate data-processing pipelines, produce geospatial visualizations, and build reusable analytical capabilities while collaborating with analysts, engineers, and mission stakeholders.

Design, implement, train, evaluate, optimize, and deploy advanced AI/ML solutions including Agentic AI, RAG, and LLMs for constrained/edge environments; translate mission stakeholder requirements into scalable, resource-aware models and recommend performance improvements.

Support critical mission systems by scoping analytical projects, developing workflow use cases, building metrics, dashboards, and visualizations, analyzing operational data for trends and improvements, and collaborating with policy and decision-making stakeholders to translate mission needs into actionable solutions.

Apply statistical, predictive, and AI/ML techniques to large-scale datasets: design, train, evaluate, deploy models; build data visualizations and analytical products; process data on distributed and cloud platforms; collaborate with stakeholders to deliver operational analytic solutions.

Design and implement scalable ETL pipelines and incremental/batch data ingestion. Perform data transformation, validation, modeling, and preprocessing using Python and SQL. Build reusable Python automation packages, automate reporting and dashboards, and document data pipelines and technical procedures.

Provide advanced discovery support using machine learning, statistical analysis, scripting, automation, and TechSIGINT tools. Develop analytical prototypes, create data visualizations, automate workflows, and collaborate with analysts and mission stakeholders to identify patterns and drive investigations.

Support CNO mission areas by applying AI/ML and Python to develop automation and analytical workflows, perform collection processing and data analysis, create and maintain Jupyter Notebooks for prototyping, and collaborate with technical and operational stakeholders while rapidly adapting to changing mission priorities.

Analyze large-scale datasets; design, develop, evaluate, and deploy AI/ML and predictive/statistical models; build data models, visualizations, and automated analytical workflows; process data using Spark and cloud platforms; apply TechSIGINT tools and provide discovery-focused analytical prototyping.

Design and automate scalable ETL/ELT and reporting workflows, perform data cleansing/validation/transformation, build reusable Python automation and SQL data-processing pipelines, support dashboard automation, improve data quality and reliability, and document data flows and processes.

Develop NLP and NER capabilities for LLM-based, Agentic AI solutions (e.g., LangGraph). Train and validate supervised and unsupervised models, build preprocessing and data-retrieval pipelines, perform automated knowledge extraction from multilingual unstructured text, integrate customer data sources, and ensure data quality, governance, and policy compliance to meet organizational and end-user needs.