Lead Data Scientist

About Tarento

Tarento is a fast-growing technology consulting company headquartered in Stockholm, with a strong presence in India and clients across the globe. We specialize in digital transformation, product engineering, and enterprise solutions, working across diverse industries including retail, manufacturing, and healthcare. Our teams combine Nordic values with Indian expertise to deliver innovative, scalable, and high-impact solutions.

We're proud to be recognized as a Great Place to Work, a testament to our inclusive culture, strong leadership, and commitment to employee well-being and growth. At Tarento, you'll be part of a collaborative environment where ideas are valued, learning is continuous, and careers are built on passion and purpose.

Job Summary

We are looking for a Lead Data Scientist to design and manage machine learning pipelines that power pricing optimization. This role focuses on handling evolving cost data, implementing robust feedback loops, and ensuring accurate model performance across multiple release cycles.

Key Responsibilities

• Design and manage ML pipelines with dynamic cost data inputs
• Develop mechanisms to detect data drift (provisional vs. confirmed data)
• Define retraining strategies and model governance protocols
• Architect data handoff processes between upstream cost systems and pricing engines
• Ensure model accuracy and prevent margin calculation errors
• Collaborate with engineering and business teams on model deployment and monitoring
  

Required Skills & Experience

• 8-12 years in data science, with focus on production ML systems
• Strong experience in pricing optimization or cost modelling
• Expertise in ML lifecycle management (training, validation, deployment, monitoring)
• Experience with data drift detection and feedback loop design
• Proficiency in Python, ML frameworks, and data engineering concepts
  

Preferred Qualifications

• Experience in supply chain, retail, or manufacturing domains
• Familiarity with large-scale data platforms and distributed systems
• Exposure to financial modelling or revenue optimization use cases