Lead Data Scientist: $105/hr
Apply Now! Job Code: 100926LDSJob Description
One of Infonet's premier clients has an opening for a Lead Data Scientist.
TERMS: Contract
SCOPE OF WORK
• Lead project teams through end-to-end data science delivery, ensuring models are technically sound, production-ready, and tied to adoption
• Data Science ownership of delivered business value: framing the right problem, building and validating ML/optimization/GenAI solutions, partnering on deployment, monitoring performance, and driving adoption in production
• Statistical and machine learning depth, combined with practical business judgment, strong stakeholder partnership, and the ability to convert analytical work into measurable outcomes rather than isolated prototypes
• Frame high-impact business problems for project-level data science leadership into measurable data science opportunities with clear decision owners, baseline metrics, adoption paths, and expected value tied to project-level improvements in revenue, demand planning, digital conversion, operational efficiency, or customer experience
• Develop forecasting, propensity, classification, and ranking models using Python, scikit-learn, XGBoost, LightGBM, CatBoost, and Databricks feature workflows to support production decisions
• Build recommendation, simulation, and optimization solutions using MILP, heuristics, dynamic programming, or scenario modeling to improve operational and commercial decisions
• Design GenAI workflows using GPT-class models, Azure AI Foundry, RAG, embeddings, prompt engineering, and evaluation routines where natural-language or agentic capabilities improve business productivity
• Design and evaluate A/B tests, quasi-experiments, causal analyses, bootstrap methods, and non-parametric tests to determine whether model or process changes create measurable lift
• Apply SHAP, sensitivity analysis, model diagnostics, error analysis, and stakeholder-ready explanations so users understand model behavior, limits, and decision implications
• Partner with AI Engineering to deploy models and analytical applications through Databricks, Azure ML, MLflow, APIs, or containerized services while retaining accountability for business value and model behavior
• Monitor accuracy, drift, bias, adoption, latency, cost, and business KPIs; trigger retraining, recalibration, or process changes when performance or value realization degrades
• Partner with business, product, operations, AI Engineering, and data engineering teams to convert model outputs into decisions, workflows, incentives, and measurable adoption
• Explain model logic, uncertainty, tradeoffs, risks, and recommended decisions in business terms
• Convert model outputs into decisions, workflows, incentives, and measurable adoption
REQUIRED SKILLS / EXPERIENCE
• Demonstrated experience appropriate to lead scope delivering ML, optimization, experimentation, or GenAI solutions that moved beyond analysis into production use or business decisioning
• Hands-on experience with Python, scikit-learn, XGBoost, LightGBM, CatBoost, PyTorch or TensorFlow where appropriate, 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
• Experience with 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 MLflow, Azure ML, model registries, CI/CD, monitoring, retraining, and production handoff practices that keep models reliable after launch
• Strong Python engineering practices, Git workflows, testing, packaging, notebooks-to-production discipline, APIs, and collaboration with AI Engineering for deployment readiness
PREFERRED EDUCATION
• 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
TRAVEL REQUIREMENT
• Some – occasionally required to walk to the dock and ascend/descend the vessel
• This position may require regular domestic or international travel
** No 3rd party vendors ** Unable to sponsor H1-B visas **
Please refer to position: 100926LDS - Lead Data Scientist: $105/hr in the subject line of all correspondence.
Please select the "Apply Now" button. We look forward to reviewing your resume and speaking with you personally.