Data Scientist

Job Responsibilities 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 Skills: Docker, Kubernetes, FastAPI, Sql, CPLEX, Pulp, Airflow, Aws, Python Experience: 3.00-10.00 Years