Top Senior Data Science Jobs in Miami, FL

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.

Build and deploy predictive models for workforce attrition, turnover, hiring, and headcount forecasting. Develop AI agents that query and act on sensitive People data, using LLMs, tool orchestration, retrieval, and guardrails. Apply experimentation, causal inference, and uncertainty quantification; extract and structure complex HR data with SQL and APIs; monitor model performance; partner with HR and Data Engineering; and explain findings to nontechnical leaders.

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.

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.

Implement metadata governance frameworks for structured and unstructured data in cloud environments. Track data lineage and synchronize metadata across data catalogs, ESRI Kubernetes, and enterprise repositories. Use OpenLineage, Apache Atlas, and related tools to manage metadata and lineage. Enforce DoD metadata policies and NSG standards for geospatial datasets while advising clients and guiding data science teams.

Lead the fraud data science team to design, build, deploy, and monitor real-time fraud detection models. Perform feature engineering, unsupervised analysis, A/B testing, stakeholder collaboration, and dashboarding to reduce fraud losses and improve model performance and explainability.

Lead and mentor data science teams to develop, validate, and deploy enterprise-scale AI/ML solutions. Collaborate with clients to define mission-focused analytics, implement Agile analytic sprints, oversee model development using Python and major ML frameworks, and leverage cloud data environments to deliver data-driven decision support under TS/SCI clearance.

The Senior Research Engineer will curate large datasets, automate data pipelines, optimize queries, and support data-driven research impacting business outcomes.

Leads ambiguous, large-scale data science initiatives across multiple teams, coordinating dependencies, timelines, and strategic execution. Establishes organization-wide data science processes and best practices, translates research into scalable solutions, mentors senior data scientists, and advises executive leadership. Requires advanced Python and SQL, expertise in machine learning, NLP, deep learning, MLOps, large-scale model deployment, monitoring, and software engineering standards.

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.

Design, train, fine-tune, deploy, and monitor Large Language Models for government mission applications. Collaborate with cross-functional teams, ensure data preprocessing and model performance, present findings to stakeholders, and mentor junior data scientists.

Lead experimentation and decision science initiatives from problem definition through recommendations. Design and analyze A/B tests, quasi-experiments, matched-market tests, and causal inference studies. Apply advanced statistics, regression, predictive modeling, machine learning, and big-data analysis using Python, R, SQL, and PySpark. Partner with stakeholders, communicate actionable findings, build reproducible workflows, and mentor analysts and junior data scientists.

Lead and build Neural Earth's geospatial data science function: design and deploy Python-based geospatial models, architect production geospatial data pipelines, validate reproducible methods, translate scientific outputs into customer-ready products, and manage and mentor at least one direct report while advising customers and stakeholders.

The Staff Data Scientist will design and optimize deep learning models for fraud detection, mentor peers, and lead data science initiatives.

Lead end-to-end predictive modeling, data-driven research, and production machine learning initiatives. Partner with senior stakeholders and engineering leaders to solve ambiguous business problems, inform strategic planning, and drive product innovation. Communicate technical findings to executive and technical audiences, architect scalable analytical solutions, mentor data scientists, and uphold rigorous data science, software engineering, and code quality standards.

Build, validate, deploy, monitor, and maintain predictive models and analytical reports. Translate findings for technical and non-technical stakeholders, promote data literacy, deliver training, collaborate on data infrastructure, apply advanced statistical and machine learning methods, and support analytical requests across mental health and crisis care programs.

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.