Data Scientist

ABOUT THE PROJECT

Our client is seeking an experienced Data Scientist to contribute to a cutting-edge data science initiative focused on advanced optimization and predictive modeling. The role supports complex analytical projects that apply mathematical programming and statistical techniques to solve real-world business problems, while also enabling knowledge transfer to internal teams.

This is a fully remote engagement offered as a one-year contract, with potential for extension.

In this role, you will design, build, and iterate on advanced optimization and predictive models, translating complex business requirements into scalable, solver-ready mathematical formulations. You will work with large datasets and complex problem spaces, applying strong analytical judgment to balance performance, accuracy, and real-world constraints.

You will be expected to operate with a high degree of independence, clearly communicate assumptions and trade-offs, and proactively drive work forward while collaborating with technical and non-technical stakeholders.

Key responsibilities include:

• Formulating and implementing optimization models, with a strong focus on mixed-integer linear programming (MILP) and related mathematical programming techniques
• Translating business objectives and constraints into solver-ready formulations and iterating on models to achieve stable, performant solutions
• Working hands-on with optimization solvers and APIs in Python (e.g., Gurobi, CPLEX, OR-Tools, PuLP/COIN-OR), including debugging and refining model behavior
• Developing and applying predictive and statistical models, including Bayesian approaches where appropriate
• Processing, cleaning, and analyzing large datasets using Python and data-wrangling libraries such as Pandas or Polars
• Supporting feature engineering and analytical workflows for large-scale optimization or modeling problems
• Implementing and maintaining data pipelines, including monitoring execution, reviewing logs, and troubleshooting performance issues
• Applying Dev Ops practices to support reproducibility, deployment, and maintainability of data science solutions
• Working with cloud-based data platforms such as Databricks and Azure Blob Storage
• Clearly communicating assumptions, methodologies, results, and trade-offs to both technical and non-technical audiences
• Producing clear documentation, model artifacts, and analytical readouts to support transparency and knowledge transfer
• Proactively identifying risks, surfacing issues early, and seeking input as needed rather than waiting for scheduled check-ins
• Supporting knowledge transfer and training for internal staff to strengthen organizational data science capabilities

Must-have:

• Demonstrated hands-on experience formulating and implementing optimization models, particularly mixed-integer linear programming (MILP)
• Strong experience translating business constraints and objectives into solver-ready mathematical formulations
• Hands-on proficiency with at least one optimization solver or API in Python (e.g., Gurobi, CPLEX, OR-Tools, PuLP/COIN-OR)
• Ability to debug, iterate, and tune optimization models to achieve stable, performant results
• Strong Python skills with experience processing and analyzing large datasets using Pandas or Polars
• Experience working with large-scale data and/or large-scale optimization problems
• Clear, structured communication skills with the ability to synthesize assumptions, approaches, results, and trade-offs
• Ability to produce high-quality written artifacts such as documentation, notes, and analytical readouts
• Self-directed, proactive working style with the ability to operate independently and surface risks early
• Experience explaining complex analytical concepts to both technical and non-technical audiences

Nice-to-have:

• Experience with Databricks, Azure Blob Storage, or similar cloud-based data platforms
• Experience implementing Dev Ops practices within data science or analytics environments
• Familiarity with Power Apps or Power Automate for workflow automation
• Experience supporting knowledge transfer, training, or enablement activities
• Exposure to production monitoring and troubleshooting of…