Top Data Science Jobs in Baltimore, MD

Seeking a skilled Data Scientist/Machine Learning Engineer to develop machine learning models, design AI systems, and collaborate in data analytics. Responsibilities include productionizing models, data engineering, and cross-functional collaboration.

As a Data Scientist at HOPPR, you'll develop and implement data pipelines and MLOps practices, utilizing large datasets and collaborating across teams to enhance AI applications in healthcare.

The Senior Applied AI Data Scientist will build AI workflows, prototype applications, and enhance decision-support systems while collaborating with various teams to operationalize AI solutions.

As a Staff Data Scientist, you will analyze large-scale broadband data, develop and validate ML models, and integrate solutions into Calix Cloud, collaborating with teams for enhanced network intelligence and subscriber experience.

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.

As a Senior Marketing Data Scientist, you will conduct quantitative analyses, manage marketing tests, and provide actionable insights to enhance marketing performance and investment effectiveness.

Analyze large marketing datasets, build predictive models for segmentation, pricing, and demand forecasting, support targeted campaigns and retention, partner with product and marketing, apply statistical and ML methods, ensure data quality with engineering, and communicate insights to stakeholders to drive conversion and retention improvements.

This role involves analyzing EHR and insurance claims data to define clinical outcomes, developing AI models, and collaborating with technical experts for manuscript preparation.

Senior individual contributor owning complex end-to-end ML problems for supply chain and consumer applications. Build and deploy predictive models (demand forecasting, delivery ETA, recommendations), embed with engineering teams, define MLOps standards, and advise leadership on data science strategy and investments.

The Data Scientist at GenLogs will build machine-learning systems, analyze large datasets, and collaborate with engineering and product teams to deliver advanced logistics intelligence solutions.

As a Data Scientist, you will analyze blockchain data to derive insights, develop and deploy predictive models, and improve product offerings.

Develop prototypes, PoCs, and MVPs for GenAI solutions. Apply deep learning and ML principles using Python, Hugging Face, LangChain, OpenAI API, TensorFlow/Keras/PyTorch, and cloud model services. Work with multi-modal data and intelligent agent tools. Be self-motivated, collaborative, and focused on solving hard AI/GenAI problems.

Design, develop, and deploy ML, NLP, and generative-AI solutions (including LLMs and RAG) to improve search, retrieval, recommendation, and question-answering across scientific publications and datasets. Build scalable pipelines, evaluation frameworks, and production-quality Python code while collaborating with engineering, product, UX, and domain experts to measure and improve model reliability, relevance, and user impact.

As a Staff Data Scientist, you'll design and optimize ML systems for claims handling automation, collaborating with product and engineering teams.

As the Staff Data Scientist, you will lead the data science function, driving strategy, mentoring peers, and shaping product direction through advanced analytics and experimentation.

The Marketing Data Scientist will analyze data, onboard clients, develop data pipelines in R, and propose improvements to enhance efficiency.

The Data Scientist will develop and improve models and LLM systems for security applications, focusing on production readiness and experimentation. Responsibilities include building classifiers and evaluating models.

Partner with Marketing as the embedded data science lead to build marketing measurement, attribution, LTV/ROAS/CAC models, run experiments, analyze the full funnel, create forecasts and dashboards, and influence channel strategy and budget allocation.

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.

Own and evolve revenue calibration models tying CX interactions to revenue, design causal inference and experimentation frameworks, build LLM-powered classification/NLP pipelines, productionize models with Analytics Engineers, define segmentation and behavioral signals, and ensure statistical rigor for executive reporting and regulatory defensibility.

As a Staff Data Scientist, you will lead product strategy by building predictive models, optimizing matching algorithms, and guiding product innovations in a consumer tech environment.

The Data Scientist role involves analyzing complex datasets, developing models, and communicating findings to stakeholders, supporting mission needs through teamwork and data-driven insights.

As a Data Scientist/Machine Learning Engineer, you'll finetune models, improve data quality, add new signals, and push solutions to production.

As Staff Data Scientist, you will drive advanced analytics to optimize sales performance, build predictive models, and develop insights for decision-making across the GTM organization.

The Staff Data Scientist will own the analytical strategy for Firefox, driving data-informed decisions through measurement frameworks, experiments, and user growth analysis, while mentoring other data scientists.