Description

 Build and maintain mathematical optimization models — objective functions, constraints, and penalty calibration

• Encode and validate business rules, contract parameters, and operational constraints into model inputs
• Execute regression testing and model health checks before and after every production run
• Conduct scenario and sensitivity analysis with documented trade-offs and business recommendations
• Validate all input files pre-run — NULL checks, format errors, anomalies, and data readiness sign-off
• Monitor data pipeline health, audit logs, and ingestion failures across recurring run cycles
• Perform data quality assessments — missingness, outliers, duplicate records, and consistency checks
• Validate model outputs and savings calculations — ensuring mathematical accuracy and business defensibility
• Review compliance and performance tracking — compare actuals vs recommendations and document deviations
• Review output files for anomalies and formatting issues before stakeholder delivery
• Support recurring run preparation — scenario setup, input file review, and run orchestration
• Triage platform issues — classify severity, gather diagnostics, and escalate with clear context
• Monitor cloud pipeline health — ingestion, compute, and delivery layer checks
• Maintain run logs, SOPs, runbooks, and knowledge base in structured auditable format
• Partner with business stakeholders to explain model outputs and recommendations in plain language
• Mentor junior team members on best practices, coding standards, and documentation discipline
  
   

Required Skills

 

• 3–8+ years experience in Data Science / Operations Research.
• Hands-on experience with optimization solvers — CPLEX and OR-Tools.(Operation Research Tools)
• Python — modeling, data validation, automation scripting, production-quality coding
• SQL — data querying, pipeline monitoring, audit log review
• Cloud platform experience — AWS or equivalent
• Strong documentation and stakeholder communication skills
  
   

Preferred Skills

 

• Pipeline orchestration tools — Dataiku, Airflow, or equivalent
• Containerization — Docker and Kubernetes
• REST API development — FastAPI or equivalent
• Open-source solver experience — PuLP, OR-Tools
• Domain knowledge in logistics, supply chain, or network optimization
• Cloud certification — AWS

Key Skills

Education

Bachelor's degree