Lead Data Scientist: Drive Bake-offs & Anomaly Detection

EPAM Systems; Argentina; Remote; ARS 900,000 - 1,400,000; Full time

Job summary

EPAM Systems seeks a Lead Data Scientist to drive core modeling execution, run bake-offs across algorithmic families, and select champion models based on rigorous evaluation. You will implement anomaly detection on historical demand data and track experiments using MLflow within the Microsoft Fabric environment.

You will partner with Data Engineering and BI teams to ensure seamless feature delivery and prediction consumption, leveraging time series forecasting, ML, and optimization techniques in

Qualifications

• Advanced degree or equivalent experience in Data Science, Statistics, OR related field.
• Expertise in time series forecasting, ML, and mathematical optimization.
• Proficiency in Python and modern ML libraries.

Responsibilities

• Run model bake-offs across algorithmic families and select champion models.
• Implement anomaly detection to identify outliers and disruptions.
• Conduct model experimentation, evaluation, and cross-validation.
• Track experiments using MLflow within Microsoft Fabric environment.
• Collaborate with Data Engineering and BI teams for feature delivery.

Skills

Time Series Forecasting

Machine Learning

Optimization

Python

LightGBM

XGBoost

Scikit-learn

Prophet

Optuna

MLflow

Tools

Walk-forward CV

Job description

EPAM Systems seeks a Lead Data Scientist to drive core modeling execution, run bake-offs across algorithmic families, and select champion models based on rigorous evaluation. You will implement anomaly detection on historical demand data and track experiments using MLflow within the Microsoft Fabric environment.

You will partner with Data Engineering and BI teams to ensure seamless feature delivery and prediction consumption, leveraging time series forecasting, ML, and optimization techniques in