Classic AI/ML Data Scientist

130 - 150 PLN/ godz./ godz.B2BB2B (netto)

SeniorZdalnieFull-time·B2B

#479903·Dodano wczoraj·1

Źródło: nofluffjobs.com

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Tech Stack / Keywords

Python SQL Machine LearningPredictive ModelingXGBoost / LightGBMscikit-learnStatistics / Statistical ModelingFeature EngineeringTime-Series ForecastingMLOps

Podsumowanie oferty

Build, validate, and deploy predictive and statistical machine learning models for business decisions, including forecasting, classification, clustering, anomaly detection, and propensity scoring. Develop models and pipelines using Python and SQL.

Wymagania

4+ years of hands-on experience building and deploying classical machine learning and statistical models in production.
Strong proficiency in Python (scikit-learn, XGBoost, LightGBM, PyTorch/TensorFlow, statsmodels, pandas) and SQL.
Solid foundation in statistics, experimental design (A/B testing), feature engineering, and model evaluation metrics.
Experience working in cloud data environments (Databricks, Snowflake, AWS, or Azure) and using MLOps tools (MLflow, Git).
Pragmatic mindset focused on choosing the simplest, most reliable model that solves the business problem.

Obowiązki

Frame business problems as machine learning tasks and conduct exploratory data analysis (EDA) on large-scale structured datasets.
Develop, train, and validate predictive models, including gradient boosting, time-series forecasting, regression, clustering, and NLP.
Build reproducible feature engineering and model training pipelines in Python and SQL.
Collaborate with Data Engineers to deploy models into production with automated monitoring for data drift and model degradation.
Communicate model insights, confidence intervals, and business impact clearly to non-technical stakeholders.

Inne informacje

During onboarding, working hours may be adjusted to overlap with US hours, until 7:00 PM at the latest.

VIRTUSA

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