Top Data Science Jobs in Baltimore, MD

Embedded data scientist working end-to-end with a business unit to define problems, build metrics, run analyses and experiments, surface insights, and drive data-informed product, growth, AI, and partnership outcomes.

Analyze microbiome and longitudinal clinical data, develop biomarkers and microbiome metrics using statistical and machine learning methods, and create visualizations, reports, protocols, and study reports. The role supports research, product development, scientific publications, proposals, and clinical studies while collaborating independently with microbiome experts in a remote-first startup environment.

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.

Lead design and evolution of large-scale nodal power market models. Define mathematical approaches, develop optimization/forecasting methodologies (MILP, SCUC/SCED), collaborate with engineers to productionize models, work with product and customers to translate market problems into software, mentor data scientists, and guide long-term product strategy.

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.

Oversee development, validation, monitoring, and governance of consumer credit risk models used for loss forecasting, credit decisioning, regulatory reporting, and risk management. Apply statistical, econometric, and machine learning methods to PD, LGD, and EAD models; support CECL, stress testing, and macroeconomic scenario analysis. Assess model performance, data quality, and compliance while communicating findings to senior leaders, auditors, regulators, and other stakeholders.

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.

Develop and evaluate Python-based machine learning models using time-series telemetry and operational data. Responsibilities include data exploration, feature engineering, NLP, probabilistic and physics-informed modeling, anomaly detection, forecasting, validation, documentation, and production deployment. Collaborate with engineering, visualization, and program teams to integrate models into dashboards and decision-support tools. The role supports DoD customers and requires U.S. citizenship plus eligibility for a security clearance.

Lead high-complexity data science initiatives improving search ranking, retrieval, relevance, and evaluation. Develop and deploy production machine-learning and NLP solutions, investigate LLM-based ranking features, optimize SQL queries, and work with sparse privacy-preserving data. Define strategies for ambiguous problems, guide other data scientists, collaborate with product teams, and own projects from scoping through production.

The Associate Data Scientist partners with clinical and operational teams to prepare and transform data, develop predictive models, apply statistical and AI techniques, and create actionable insights. Responsibilities include feature engineering, model optimization, data visualization, dashboards, stakeholder presentations, risk management, and Agile collaboration to improve patient care, hospital operations, and organizational outcomes.

Lead development and deployment of large-scale LLM and GenAI solutions for cybersecurity. Drive research strategy, model training, evaluation, safety/red-teaming, and cross-functional productization. Mentor data scientists, set technical standards, and represent the team through publications and thought leadership.

Develop and refine predictive models, perform exploratory data analysis, and generate AI-driven insights for DoD missions. Integrate multi-source data, apply geospatial analytics, iterate models via Agile sprints, produce performance and cost reports, and optimize analytic workflows for operational deployment.

Develop and maintain predictive pricing, retention, and conversion models using GLMs and advanced analytics; build monitoring tools for rating performance; support rate filings, product pricing analyses, competitor research, and cross-functional collaboration to inform pricing and enterprise risk decisions.

The Data Scientist will analyze data for risk and trading in Daily Fantasy Sports, develop predictive models, and monitor real-time data.

Develop and maintain reproducible bioinformatics pipelines and multi-omics data products. Perform statistical modeling, ML, and integration of genomic, transcriptomic, spatial, proteomic, and clinical datasets. Build researcher-facing dashboards, notebooks, and APIs; ensure FAIR, containerized, version-controlled analyses; collaborate with scientists, engineers, and government stakeholders to enable reusable, secure, analysis-ready data workflows.

Assists with analyzing complex datasets, developing predictive models for insurance underwriting, pricing, claims, and retention, and building data pipelines and automated reporting. Collaborates with actuarial, underwriting, claims, product, and data engineering teams to solve business problems. Communicates insights through visualization and data storytelling, monitors model performance and data quality, and explores new data sources and modeling techniques while supporting insurance model governance.

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.

Analyze, clean, and validate complex healthcare data; develop statistical, machine learning, and AI models; implement agentic workflows, RAG solutions, and model fine-tuning; deploy and monitor models in production; collaborate with technical and business teams; conduct research; and document and communicate findings.

Design and build thermal performance analytics, Python-based engineering models, scalable data flows, and Edge-native applications for power plant asset performance management. Integrate historian, cloud, Edge, and industrial systems; develop automation, diagnostics, KPI validation, and root-cause workflows; support customer deployments; and lead architecture discussions while mentoring engineering teams.

Supports data processing, statistical and machine learning model updates, marketing analyses, reporting, and data automation. Uses R or Python, SQL, BigQuery, BI tools, and spreadsheets to prepare datasets, maintain media-mix models, analyze results, and communicate insights to technical and non-technical audiences. Collaborates with Engineering, Reporting, Product, Paid Media, and Data Science teams while developing advanced analytical skills.

Lead research and experimentation to measure ad campaign performance and effectiveness. Design evaluation frameworks, build measurement solutions, develop models for lift, conversion, and attribution, run experiments and analyses, partner with product/engineering/design/sales, present insights, mentor teammates, and foster technical community and culture.

Lead design and execution of scalable experimentation frameworks for Netflix Ads. Develop auction-based, biddable media models, solve cold-start measurement problems globally, apply causal inference and ML, partner with product and engineering, and translate analytic results into strategic recommendations to optimize marketplace dynamics and member experience.

Lead design, execution, and interpretation of A/B tests and quasi-experiments; apply causal inference methods; partner with product, engineering, and marketing; mentor data scientists; build experimentation frameworks; extract and analyze data using SQL and Python; communicate results to stakeholders.

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.