Decision Scientist

120 - 140 PLN/ godz./ godz.B2BB2B (netto)

SeniorZdalnieFull-time·B2B

#478996·Dodano 2 dni temu·0

Źródło: nofluffjobs.com

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Tech Stack / Keywords

PythonOperations ResearchMathematical OptimizationLinear Programming (LP / MILP)PyomoGurobi / GLPKMachine learningStatistical ModelingSupply Chain AnalyticsGit Azure Databricks PySpark Apache SparkDelta LakeUnity CatalogNeo4jCypher

Podsumowanie oferty

Develop and support analytical solutions for supply risk sensing and procurement intelligence initiatives. The role focuses on mathematical optimization, applied machine learning and statistics, and production-quality Python.

Wymagania

Master's degree in Operations Research, Industrial Engineering, Applied Mathematics, Statistics, Computer Science, or a similarly quantitative field.
4+ years of hands-on experience building analytical, OR, or ML solutions, ideally in supply chain, manufacturing, logistics, procurement, or other operational environments.
Strong fundamentals in optimization modeling, including LP/MILP formulation, solver behavior, and practical infeasibility handling.
Hands-on applied ML/statistical modeling experience, including feature engineering, model training, validation design, metric selection, and interpretation of results.
Strong Python proficiency, including pandas, NumPy, and analytical libraries, and experience writing maintainable code beyond exploratory prototypes.
Hands-on experience with Pyomo and LP/MILP solvers such as GLPK or Gurobi.
Ability to understand, debug, and extend existing code and analytical models, and communicate technical design and results clearly to the project team.

Nice to have:

Experience with Azure Databricks, PySpark/Spark, Delta Lake, and Unity Catalog.
Background in supply network modeling, multilevel bills of materials, inventory optimization, disruption simulation, or graph-based analysis; Neo4j/Cypher is a plus.
Experience with time-series forecasting, anomaly detection, and ML ranking/recommendation methods.
Experience in pharmaceutical/life sciences supply chains or exposure to GenAI-enabled analytics and conversational insights.

Obowiązki

Develop and enhance mathematical optimization (LP/MILP), simulation, time-series, statistical/ML, and network-based analytical models as required by the use case.
Formulate analytical problems, including decision variables, objective functions, constraints, assumptions, and treatment of infeasibility or trade-offs.
Work with existing Python analytical pipelines and Databricks notebooks; trace dependencies across data transformations, model logic, and downstream outputs before making changes.
Prepare and validate analytical inputs from demand forecasts, inventory, bills of materials, supplier data, and other operational datasets.
Develop, train, and evaluate ML models for classification, forecasting, anomaly detection, and ranking when supported by available data.
Validate solutions through testing, scenario/sensitivity analysis, and business-result reconciliation.
Write modular, maintainable, testable Python code; document model logic, implement regression tests, use version control, and troubleshoot data, model, and runtime issues.
Collaborate with the Decision Science, Data Engineering, and Technology teams on implementation dependencies, testing, and production readiness.

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