Lead Data Scientist

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

We are seeking a Lead Data Scientist to drive core modeling execution, including running competitive model bake-offs, selecting champion models, performing model evaluation, and implementing anomaly detection.ResponsibilitiesConduct model experimentation and bake-offs across multiple algorithmic families (tree-based regressors, statistical forecasting, deep learning, optimization)Select and justify the champion model based on cross-validation and business-defined error metricsImplement anomaly detection algorithms to identify outliers and operational disruptions in historical demand dataTrack and log experiments using MLflow within the Microsoft Fabric environmentPartner with Data Engineering and BI teams to ensure seamless feature delivery and prediction consumptionRequirementsAdvanced degree or equivalent experience in Data Science, Statistics, Operations Research, or Computer ScienceExpertise in Time Series Forecasting, Machine Learning, and mathematical optimizationProficiency in Python and modern ML libraries such as LightGBM, XGBoost, and Scikit-learnFamiliarity with Prophet and OptunaExperience with experiment tracking using MLflow and validation methodologies such as walk-forward CVProfessional English proficiency (B2+/C1)We offerInternational projects with top brandsWork with global teams of highly skilled, diverse peersHealthcare benefitsEmployee financial programsPaid time off and sick leaveUpskilling, reskilling and certification coursesUnlimited access to the LinkedIn Learning library and 22,000+ coursesGlobal career opportunitiesVolunteer and community involvement opportunitiesEPAM Employee GroupsAward-winning culture recognized by Glassdoor, Newsweek and LinkedIn