Senior Data Scientist

At Global IT Hub, we are more than a technology organization. We are a community of innovators, problem-solvers, and digital pioneers dedicated to accelerating Atlas Copco Group’s business potential through world-class technology solutions. Join us to shape the future of digital transformation, work on global challenges, and create impact for businesses and customers worldwide.

CLASSICAL MACHINE LEARNING | JOB DESCRIPTION

Role purpose Lead the design, validation, deployment and lifecycle ownership of production-grade classical machine learning solutions that convert business problems into measurable outcomes. The role combines deep algorithmic expertise, disciplined CRISP-DM execution, MLOps practices and senior technical leadership.

Role at a glance

Team

AI Team, Global IT Hub

Primary Stakeholders

Business product owners, IT, data engineering, analytics and domain teams

Experience

5+ years in data science / machine learning, including 3+ years owning production ML solutions

Education

Bachelor’s or Master’s degree in Data Science, Statistics,



Mathematics, Computer Science, Engineering or a related quantitative field

Key responsibilities

• Partner with stakeholders to frame ambiguous business needs as well-defined machine learning problems, including decision context, baselines, constraints, risks and measurable success criteria.
• Lead end-to-end delivery using CRISP-DM: business understanding, data understanding, data preparation, modeling, evaluation and deployment, with iteration and traceability across phases.
• Design, train and compare classical supervised and unsupervised learning models; select the simplest approach that meets performance, interpretability, latency, scalability and cost requirements.
• Own feature engineering, data leakage prevention, sampling strategy, cross-validation, hyperparameter optimization, threshold selection, calibration and robust error analysis.
• Build reliable evaluation frameworks using fit

📌 Senior Data Science (India)
🏢 Atlas Copco Group
📍 India