**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 transparent 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**

📌 Data Scientist (Bengaluru)
🏢 Ascendion Engineering
📍 Bengaluru