Lead Data Scientist

Eightelevengroup; Miami, Northern (FL, KY); Hybrid; USD 110,000 - 131,000; Full time

Benefits offered by this job

Health insurance

401(k) plan

Paid time off

Holidays

Job summary

Eight Eleven Group's client is seeking a Sr. Data Scientist to lead end-to-end data science initiatives in a hybrid Miami role. You will own problem framing, build and deploy models using Python and ML libraries, and drive adoption with measurable business impact.

You will work with Databricks, Azure AI Foundry, MLflow, and GenAI workflows, ensuring model explainability and high performance in production across teams and environments.

Qualifications

• Senior-level ML/DS experience with production delivery.
• Ability to frame problems and translate to business value.
• Experience with GenAI workflows and model explainability.

Responsibilities

• Frame problems for senior model ownership with measurable value.
• Develop, validate, and deploy predictive models in production.
• Design prescriptive analytics and GenAI workflows for automation.
• Monitor models for drift and performance; trigger retraining.
• Collaborate with cross-functional teams to turn outputs into decisions.

Skills

Python

ML Libraries

GenAI

Model Deployment

Communication

Education

Bachelor's or Master’s in CS/Stats/Data Science

Tools

Databricks

Azure ML

MLflow

XGBoost

LightGBM

CatBoost

Job description

Sr. Data Scientist

Hybrid Role - Miami, FL

Compensation: $80 - $95 per hour

ABOUT THE ROLE

Our client is seeking a Sr. Data Scientist to lead complex, end-to-end data science initiatives—from business problem framing through production deployment and operational monitoring. This role emphasizes full ownership of delivered business value: identifying and framing high-impact problems, developing and validating machine learning, optimization, and generative AI solutions, and ensuring their adoption and measurable impact across the organization. The Sr. Data Scientist will partner closely with cross-functional teams to translate analytics into actionable business decisions, drive model explainability and trust, and maintain ongoing model performance. You will utilize advanced tools and platforms including Python, scikit-learn, XGBoost, LightGBM, CatBoost, Databricks, Azure AI Foundry, and MLflow. The position may require domestic or international travel and the ability to work in both office and shipboard environments.

WHAT YOU'LL DO

• Frame high-impact business problems for senior model ownership, translating them into measurable data science opportunities with clear decision owners, baseline metrics, adoption paths, and expected value tied to improvements in revenue, cost, service, capacity, personalization, or operational decision quality.
• Develop, validate, and deploy predictive models (forecasting, propensity, classification, ranking) using Python and modern ML libraries (scikit-learn, XGBoost, LightGBM, CatBoost) and Databricks feature workflows to support production decisions.
• Design and implement prescriptive analytics solutions, including optimization (MILP, heuristics, dynamic programming), simulation, and scenario modeling to improve operational and commercial outcomes.
• Build and evaluate GenAI workflows leveraging GPT-class models, Azure AI Foundry, RAG, embeddings, prompt engineering, and evaluation routines to enhance business productivity and workflow automation.
• Design and analyze statistical experiments (A/B tests, quasi-experiments, causal analyses, bootstrap methods, non-parametric tests) to assess the impact of models and process changes.
• Ensure model explainability and trust through SHAP, sensitivity analysis, model diagnostics, error analysis, and clear, stakeholder-ready communication of model behavior, limitations, and decision implications.
• Partner with AI Engineering to deploy models and analytical applications through Databricks, Azure ML, MLflow, APIs, or containerized services, maintaining accountability for business value and model behavior in production.
• Monitor production models for accuracy, drift, bias, adoption, latency, cost, and business KPIs; trigger retraining, recalibration, or process changes as needed to ensure ongoing value realization.
• Collaborate with business, product, operations, AI Engineering, and data engineering teams to convert model outputs into decisions, workflows, incentives, and measurable adoption.

WHAT YOU BRING

• Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Operations Research, Engineering, Economics, or a related quantitative field, or equivalent practical experience.
• Demonstrated senior-level experience delivering ML, optimization, experimentation, or GenAI solutions in production environments, with a track record of moving beyond analysis to business decisioning and measurable outcomes.
• Hands‑on experience with Python, scikit‑learn, XGBoost, LightGBM, CatBoost, PyTorch or TensorFlow, and model evaluation workflows for production‑grade use cases.
• Experience with MILP solvers, simulation, scenario planning, dynamic programming, heuristics, or prescriptive analytics methods applied to real business decisions.
• Proficiency with GenAI platforms (Azure AI Foundry, GPT‑class models, RAG, embeddings, prompt engineering, evaluation) and safe use of GenAI for decision support or workflow automation.
• Advanced use of Databricks, Spark, SQL, feature pipelines, data quality checks, and reproducible analytical workflows for large‑scale data science delivery.
• Experience with MLOps tools (MLflow, Azure ML, model registries, CI/CD, monitoring, retraining, production handoff) to ensure models remain reliable after launch.
• Strong Python engineering practices, Git workflows, testing, packaging, notebooks‑to‑production discipline, APIs, and collaboration with AI Engineering for deployment readiness.
• Clear communication skills with technical and business stakeholders, including the ability to explain model logic, uncertainty, tradeoffs, risks, and recommendations in business terms.
• Ability to travel domestically and internationally as required by the role, and to work in both office and shipboard environments.
• Compliance with company COVID‑19 vaccination policy (or approved accommodation).

WHAT'S IN IT FOR YOU

• Opportunity to lead high‑impact data science initiatives with end‑to‑end ownership and measurable business value.
• Collaborative, cross‑functional environment with exposure to advanced AI, ML, and GenAI technologies.
• Hybrid work arrangement and the potential for domestic and international travel.
• Comprehensive support for professional growth and development.
• Commitment to equal employment opportunity and a diverse, inclusive workplace.
• Guidance and support from recruiters throughout the application process.

Brooksource, Medasource, and Calculated Hire are part of the Eight Eleven Group family of companies and operate under Eight Eleven Group, LLC. All employees receive the same benefits, policies, and terms of employment.

EEO:

We are committed to creating an inclusive environment for all employees and applicants. We do not discriminate on the basis of race, color, religion, creed, sex, sexual orientation, gender identity or expression, national origin, ancestry, age, disability, genetic information, marital status, military or veteran status, citizenship, pregnancy (including childbirth, lactation, and related conditions), or any other protected status in accordance with applicable federal, state, and local laws.

Benefits & Perks:

Brooksource offers competitive medical, dental, vision, Health Savings Account, Dependent Care FSA, and supplemental coverage with plans that can fit each employee’s needs. We offer a 401k plan that includes a company match and is fully vested after you become eligible, paid time off, sick time, and paid company holidays. We also offer an Employee Assistance Program (EAP) that provides services like virtual counseling, financial services, legal services, life coaching, etc.

Pay Disclaimer:

The pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.