Sr. Data Scientist

Sr. Data Scientist Miami, FL - Hybrid 6-Month CTH on W2 $70-75/hr POSITION SUMMARY We are seeking a Sr. Data Scientist to serve as a senior owner for production data science outcomes, combining advanced modeling, experimentation, optimization, and stakeholder leadership to deliver measurable value across business processes. This role is accountable for senior independent model ownership and cross-functional influence and is expected to operate at the level of 4–8 production models, decision engines, experiments, or GenAI workflows across one or more domains, with influences experimentation cost, model operating cost, and build-versus-buy recommendations for owned work. The role differentiates Data Science ownership of problem framing, model behavior, experimentation, value measurement, adoption, and production model health from AI Engineering ownership of scalable platform foundations. The candidate will partner closely with domain leaders, product owners, AI engineers, data engineers, and senior business stakeholders to convert analytical rigor into decisions, workflow change, and measurable performance improvement. ESSENTIAL RESPONSIBILITIES • Problem Framing & Value: Own problem framing for 4–8 production models, decision engines, experiments, or GenAI workflows across one or more domains by quantifying baselines, decision points, adoption paths, and expected value before modeling begins, with outcomes tied to multi-process improvements in revenue, cost, service, capacity, personalization, or operational decision quality. • Predictive Modeling: Develop and validate high-performing predictive models using Python, scikit-learn, XGBoost, LightGBM, CatBoost, Databricks, feature stores, and robust backtesting appropriate to production decisioning. • Prescriptive Decisioning: Design optimization, recommendation, simulation, or scenario-planning engines that translate predictions into actions, constraints, tradeoffs, and measurable operational or commercial lift. • GenAI Solutions: Build GenAI use cases with GPT-class models, Azure AI Foundry, RAG, embeddings, prompt libraries, evaluation harnesses, and safety tests, focusing on business process improvement rather than novelty. • Statistical Experimentation: Lead experimentation strategy using A/B tests, causal inference, quasi-experimental designs, bootstrap methods, and sensitivity analysis to prove whether interventions drive incremental value. • Explainability & Trust: Create trust mechanisms using SHAP, counterfactual analysis, model cards, residual/error analysis, human review loops, and stakeholder-ready narratives that expose limitations and decision implications. • Production Deployment: Partner with AI Engineering to productionize models through Databricks, Azure ML, MLflow, APIs, batch scoring, or containerized services while maintaining ownership of model quality, value, and adoption. • Production Operations: Own post-launch model health by monitoring accuracy, drift, calibration, bias, adoption, financial KPIs, latency, and cost, then driving retraining, rollback, or operating-process changes when needed. • Stakeholder Partnership: Lead cross-functional adoption with business, product, operations, AI Engineering, and data engineering teams so model outputs become decisions, workflow changes, and measurable performance improvements. QUALIFICATIONS / KNOWLEDGE / SKILLS • Education: Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Operations Research, Engineering, Economics, or related quantitative field, or equivalent experience delivering production models at comparable scale. • Experience: Proven experience at senior scope delivering 4–8 production models, decision engines, experiments, or GenAI workflows across one or more domains, including production use, stakeholder adoption, value tracking, model operations, and measurable improvement in business outcomes. • ML Tooling: Advanced experience with Python, scikit-learn, XGBoost, LightGBM, CatBoost, PyTorch/TensorFlow where relevant, model evaluation, hyperparameter tuning, backtesting, and feature engineering. • Optimization: Strong experience applying MILP, simulation, dynamic programming, heuristics, stochastic methods, or prescriptive analytics to constrained, high-value business decisions. • GenAI Platforms: Advanced experience with Azure AI Foundry, GPT-class models, RAG quality measurement, embeddings, prompt/version control, evaluation, safety testing, and workflow automation. • Data Platforms: Deep hands-on experience with Databricks, Spark, SQL, feature stores, data quality checks, reproducibility patterns, and large-scale analytical pipelines. • MLOps: Advanced experience with MLflow, Azure ML, model registries, CI/CD gates, monitoring, retraining triggers, rollback plans, and production ownership routines. • Engineering: Strong production-oriented Python discipline, including modular code, testing, Git workflows, packaging, APIs, documentation, and collaboration with AI Engineering on scalable deployment patterns. • Communication: Executive-ready communication skills tailored to domain leaders, product owners, AI engineers, data engineers, and senior business stakeholders, with the ability to translate statistical uncertainty, model tradeoffs, risk, and value into clear decisions. Disclaimer: 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.