Top Senior Data Science Jobs in Baltimore, MD

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.

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.

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.

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.

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.

Develop and improve NLP solutions for spoken and written language data, including automated tokenization and linguistic annotation, analyze speech/text datasets, evaluate model performance against human annotations, and document methods and recommended improvements.

Provide advanced discovery and analytical support using machine learning, statistical analysis, scripting, automation, and TechSIGINT tools. Develop analytical prototypes, create data visualizations, document methods and collaborate with analysts and engineers to support mission-focused discovery efforts and adopt new analytical technologies.

Design and deploy predictive forecasting and analytics to support Revenue operations. Build models for forecasting, churn, expansion, and pipeline analytics; create scalable dashboards; partner with Revenue Operations, Finance, and Data Engineering to improve data quality, KPI governance, and executive reporting to drive data-driven decisions and AI readiness.

Own end-to-end modeling for vendor matching, order routing, and supply-chain optimization. Build predictive, causal, RL and OR solutions; design autonomous decision logic; quantify counterfactual impact; ship production models with data engineering; mentor senior data scientists; write technical design docs; partner on quarterly priorities and expand into revenue cycle and finance domains.

Senior individual contributor who drives product analytics, experimentation, and applied modeling. Owns growth and performance analyses, designs experiments with robust statistical evaluation, builds repeatable reporting, and partners with Product, Engineering, Operations, Clinical, and Finance to translate data into actionable product and operational decisions.

Build and scale production-ready generative AI applications: design multi-agent workflows, implement advanced RAG with vector DBs, integrate/swap LLMs, fine-tune models, and deploy scalable FastAPI/Docker services with monitoring and optimization for latency, cost, and reliability.

Build and scale production Generative AI applications: design multi-agent systems and LangGraph workflows, implement advanced RAG with vector DBs, integrate and fine-tune LLMs, deploy FastAPI async services in Docker, and optimize GenAI performance, cost, and monitoring.

Design, build, and deploy production-ready generative AI applications: architect multi-agent workflows, implement advanced RAG with vector DBs, integrate/swap LLMs, fine-tune models, and deliver scalable FastAPI-based services with monitoring, CI/CD, and containerized deployment.

Design, build, and deploy machine learning and generative AI models (including LLMs and text-to-image). Analyze large datasets, run A/B and statistical tests, collaborate with data engineering and engineering teams, and create dashboards/visualizations to communicate insights. Optimize data pipelines and model performance to support data-driven decisions.

Owner of analytics for EHR, revenue cycle, and operations: design and run experiments, analyze financial and operational metrics, investigate billing and account issues, and deliver actionable insights to Product, Operations, Finance, and Customer Experience to improve accuracy, reduce friction, and support growth.

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.

Perform advanced data exploration, engineering, and machine learning within Palantir Foundry. Develop Foundry applications, pipelines, and workflows; implement DevSecOps and CI/CD; engage stakeholders to translate requirements into technical solutions for Department of War clients. Work in agile teams supporting scalable analytics platforms; a Secret clearance is required.

Design and prototype statistical, graph-based, and machine learning algorithms to analyze disparate datasets, validate analytics, produce visualizations, and collaborate with engineers and threat analysts to operationalize scalable solutions in a cybersecurity mission environment.

Designs, analyzes, and interprets clinical trial, RWE, and observational data for a medical device. Develops statistical plans, predictive models, and ensures data quality, regulatory compliance, and traceability. Collaborates with clinical, regulatory, and data teams, supports submissions and publications, mentors interns, and represents the company externally.

Design, implement, and maintain marketing inference models (e.g., MMM and attribution). Analyze large datasets and A/B/uplift experiments with rigorous statistics, build predictive and causal models, partner with marketing to generate testable ideas, and communicate insights to drive marketing decisions.