Top Data Science Jobs in Miami, FL

As a Data Scientist at SentiLink, you'll develop fraud detection models using machine learning, engage in product development, and support analysis across teams. This role emphasizes hands-on technical work and end-to-end project ownership in a fast-paced environment.

Design and train LLMs and agentic systems for cybersecurity using RLHF/RLAIF and supervised fine-tuning. Build agent architectures, tooling, retrieval/memory, and evaluation pipelines with rigorous statistical benchmarking. Optimize prompts and inference, collaborate with engineers to productionize prototypes, and drive research on agent planning, safety, and reliability.

Analyze complex datasets, build predictive models, and communicate findings to stakeholders while collaborating with data engineers and quantitative researchers.

This role involves applying advanced data science and machine learning methods to healthcare data, leading teams, managing client relations, and developing analytics products for payers, while mentoring junior staff.

As a Staff Data Scientist at SentiLink, you will develop fraud detection models, conduct analyses, collaborate across teams, and drive the development of financial risk products.

Lead end-to-end data science projects, develop machine learning models, collaborate with stakeholders, mentor team members, and communicate insights effectively.

Design and run advanced statistical and machine learning analyses on large healthcare datasets to evaluate programs, inform policy, and produce visualizations and reports. Collaborate with clinical, policy, and IT teams, ensure data quality and privacy compliance, mentor junior analysts, and translate findings into actionable recommendations to improve care delivery.

The Data Scientist will support intelligence operations by applying advanced analytics to complex datasets, develop models, and collaborate with teams to enhance mission delivery.

Develop, test, and deploy machine learning and NLP solutions using structured and unstructured data. Clean and integrate data, iterate on AI agents and pipelines, support model monitoring and experimentation, collaborate with engineering and cross-functional teams, and communicate technical findings to non-technical stakeholders.

As a Staff Data Scientist, you will develop data-driven fraud prevention solutions using Generative AI, design scalable ML pipelines, and mentor junior data scientists while collaborating across teams to improve analytics and decision-making.

Lead product analytics to inform strategy and optimize user experience: translate business questions into analysis, build reliable analytics infrastructure, run A/B tests and ML/statistical analyses, track funnels and cohorts, support 0-to-1 product launches, and communicate actionable insights to cross-functional teams.

The Principal ML Engineer at Agero will develop and productionize a Dispatch System using ML models, optimize decision-making processes, and lead a team to improve operational performance.

The Principal Data Scientist will lead data analysis projects, collaborate with product management, assess business impacts, ensure data governance, and mentor junior analysts. Must leverage statistical techniques and machine learning to drive product strategy and business outcomes.

Lead ownership of marketing measurement: design data pipelines, build and productionize MMM and LTV models, run incrementality and geo-lift experiments, produce scenario analyses and dashboards, and influence media investment decisions across marketing and executive stakeholders.

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

Lead the fraud data science function: define ML strategy, build and productionize fraud detection models, investigate fraud patterns, run experiments, collaborate with Product/Engineering/Risk, and deliver dashboards and monitoring to minimize fraud losses while preserving customer experience.

Lead the fraud data science effort: define ML strategy, build and productionize real-time fraud detection models, investigate fraud patterns with unsupervised and graph techniques, run experiments, collaborate with product/engineering/risk, and maintain dashboards to monitor model performance and fraud KPIs.

Lead Fraud Data Scientist to define ML strategy, build and productionize fraud detection models (including lending fraud), run advanced analyses and A/B tests, mentor the team, integrate ML with rule engines, and create dashboards to monitor fraud KPIs and model performance.

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.

Lead strategy and execution for generative and multimodal vision systems, from research to production. Design model architectures, adaptation, evaluation, and deployment pipelines; improve realism, controllability, robustness, and temporal consistency; benchmark and guide model selection; mentor scientists and coordinate cross-functional engineering to ship production-ready AI capabilities.

Build, evaluate, and ship matching, recommendation, and ranking models for job-seeker experiences. Work with skills and occupation taxonomies and labor-market data, partner with Engineering to productionize and monitor models, and translate messy data into clear, actionable analysis for product and customers.

Design, build, and deploy predictive GTM models (LTV, attribution, propensity). Lead experimentation and causal analyses, define KPI measurement frameworks, partner with Data Engineering, and translate statistical insights into actionable recommendations for Sales, Marketing, and Customer Success.

Develop and tune ML models, productionize and deploy strategies for ML systems, and align cross-functionally to communicate performance metrics.

Embed within GTM Marketing to design experiments, build attribution, propensity, churn, segmentation, and conversion models; analyze product engagement and organic search signals; partner with analytics engineers to productionize models; and translate statistical results into actionable business recommendations.

Lead healthcare and pharmaceutical marketing analytics: analyze CRM, media, healthcare and behavioral data; build segmentation, attribution, audience scoring, and predictive models; develop measurement frameworks; use Python, SQL, BI and automation; translate insights for executives; mentor juniors and partner with Strategy, Media, and Client Services.