Top Data Science Jobs in Baltimore, MD

Analyze large structured and unstructured datasets, develop and deploy statistical and machine learning models, build/automate data processing workflows, create visualizations and dashboards, and communicate findings to technical and non-technical stakeholders in support of IC and DoD missions.

Develop and maintain advanced data processing, entity resolution, and data cleansing pipelines using Python and SQL. Responsibilities include NLP, information extraction, data validation, query optimization, testing, deployment, monitoring, code reviews, and maintaining data integrity, privacy, security, and reproducibility. The role requires expertise in record linkage, named entity recognition, text processing, matching strategies, and machine learning libraries, with on-site work at SSA headquarters in Woodlawn, Maryland.

Develop and optimize machine learning and statistical models for fraud detection and anti-money laundering. Analyze large datasets to identify fraudulent patterns, build scalable data pipelines and features, evaluate model performance, and collaborate with engineering, product, and operations teams. Communicate insights to technical and non-technical stakeholders while maintaining data privacy and security compliance. The role offers significant ownership in building Oscilar’s early machine learning stack within a remote-first startup.

Support defense cybersecurity efforts by mapping and curating large datasets, applying AI/ML (including generative AI) and statistical methods, building models and visualizations/dashboards, documenting metrics, and communicating analytic conclusions to technical and non-technical stakeholders.

Design, build, evaluate, and productionize agentic AI, LLM, RAG, and predictive ML systems for scientific information products. Develop training and inference pipelines, fine-tune models, establish trustworthy-AI evaluation and safeguards, and operate AI capabilities at scale. Set engineering standards, lead technical initiatives, mentor scientists and engineers, influence product and executive decisions, and communicate results through presentations, publications, and client engagements.

Tune AML and fraud detection models using customers’ live transaction data. Investigate missed cases, alert quality, pattern drift, and false positives; validate changes through backtesting and sample review; document regulatory rationale; and present model performance and business value to compliance, risk, and data science stakeholders. Partner with customer teams on account strategy and relay customer-specific or systemic findings to product and model functions.

Own mobile marketing analytics frameworks, dashboards, cohort and campaign analysis, profitability modeling, audience strategy, and incrementality experiments. Analyze attribution, retention, LTV, CAC, ROAS, payback, creative performance, and marketplace dynamics. Partner with marketing, finance, and leadership to guide spend allocation and growth decisions while navigating mobile privacy and attribution challenges.

Own sales forecasting and revenue analytics by developing statistical and machine learning models across products, regions, and time horizons. Lead the full machine learning lifecycle from feature engineering through deployment, monitoring, and explainability. Translate forecasts into business recommendations, deliver production data products, mentor junior data scientists, and provide technical leadership across analytics and sales 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.

The internship offers military service members civilian work experience in data science through data analysis and related skillsets over 90-180 days.

Leads end-to-end applied data science and AI workstreams for predictive underwriting and pricing, including problem framing, feature engineering, model development, validation, deployment, monitoring, and business-impact measurement. Builds explainable, governed, and reusable production models using healthcare and insurance data. Partners with underwriting, business, product, engineering, and legal teams; mentors others; and advances responsible AI, MLOps, model governance, and shared data science practices.

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

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.

Develop machine learning and AI models using clinical, claims, and social determinants of health data to improve pediatric patient outcomes. Partner with stakeholders and cross-functional teams to define requirements, optimize data collection, build data assets, conduct exploratory analysis, and deliver strategic and patient-care insights. Query Snowflake independently and present findings to nontechnical staff.

Develop and validate predictive and prescriptive machine learning models for cyber defense decision-making. Perform statistical analysis, anomaly detection, event correlation, and operational research to identify trends and characterize threats. Translate mission requirements into analytic solutions, document methodologies, and mentor junior data scientists. The role requires advanced Python, R, and SQL skills, model deployment experience, strong statistical expertise, and a Top Secret clearance with the ability to obtain and maintain SCI eligibility.

Develop AI tools, machine learning systems, predictive analytics, data visualizations, and large-scale Multi-INT data fusion capabilities for USCYBERCOM J2 intelligence operations. Analyze and merge disparate data using R, Python, and SQL; create Power BI and Tableau visualizations; produce analytic reports; and collaborate with intelligence stakeholders to prioritize capability gaps.

The Data Scientist will design and deploy AI-enabled data solutions, developing data pipelines and collaborating with teams to transform data into insights.

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

The Data Scientist Level 3 will use mathematical, statistical, and computational skills to analyze large datasets, derive insights, and communicate results to both technical and non-technical audiences.

Apply AI/ML and NLP techniques to analyze, triage, and characterize large language datasets. Develop and train models, create analytical tools, perform data mining and qualitative characterization, evaluate model performance, document methodologies, and collaborate with technical and mission teams to support operational objectives.

Perform research and analytical work to support targeting, access discovery, and mission-focused research. Analyze complex datasets, develop models, and produce visualizations. Apply computational mathematics and Python-based analytics, document methodologies, and collaborate with technical and mission teams to support operational objectives.

Design, implement, and deploy AI/ML solutions and autonomous agents using LLMs, reinforcement learning, and agentic AI. Optimize and scale neural models, apply prompt engineering and RAG, document results, follow software development best practices, and collaborate with mission teams to support operational objectives.

Develop automated security evaluation and authorization capabilities using Python, statistical analysis, machine learning, anomaly detection, and ETL pipelines. Build reliable dataflows integrating network, security, and compliance data to support continuous monitoring, RMF automation, reporting, and security decision-making. The role requires extensive analytics and programming experience and a TS/SCI clearance with polygraph.

Analyze, manipulate, and visualize complex mission data to support AWCP activities; develop analytical methods, workflows, and visualizations; research and correlate multi-source information; document findings and collaborate with technical and mission teams.