Ascendion - Data Scientist - Operations Research

Role: Data Scientist Location: Bengaluru, India 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. Required Skills: - Hands-on 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. Role: Data Scientist Location: Bengaluru, India 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. Required Skills: - Hands-on 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.