Senior Data Scientist: Should-Cost & Procurement Analytics

EPAM Systems; United States; Remote; USD 120,000 - 190,000; Full time

Job summary

EPAM Systems in the United States is seeking a Senior Data Scientist to build data-driven should-cost models using time-series and econometric methods for procurement analytics. You will analyze macroeconomic factors, model relationships between prices and spend data, and ensure explainability of outputs for stakeholders.

You will apply time-series validation and guard against leakage and overfitting. English proficiency and deep experience in data science are expected to drive actionable

Qualifications

• 3+ years of experience in data science focused on time-series and econometric modeling.
• Proficiency in Python, Prophet and Chronos for forecasting.
• Experience with procurement analytics, spend data and commodity indexing.
• Knowledge of economic indicators, spend analysis and supplier metrics.

Responsibilities

• Develop 'should-cost' models using time-series and econometric methods.
• Incorporate macroeconomic factors and indicators as drivers of cost.
• Model relationships between commodity prices, spend data, and external variables.
• Make model outputs explainable to stakeholders, detailing driving factors.
• Apply time-series cross-validation to ensure robustness.
• Prevent data leakage and overfitting in time-series models.
• Differentiate correlation from cointegration and apply appropriately.
• Select relevant features for time-series and econometric models.

Skills

Time-series modeling

Econometric modeling

Explainable AI

Procurement analytics

Tools

Python

Prophet

Chronos

Job description

EPAM Systems in the United States is seeking a Senior Data Scientist to build data-driven should-cost models using time-series and econometric methods for procurement analytics. You will analyze macroeconomic factors, model relationships between prices and spend data, and ensure explainability of outputs for stakeholders.

You will apply time-series validation and guard against leakage and overfitting. English proficiency and deep experience in data science are expected to drive actionable