Lead Data Scientist

About the Company

KSB Tech is the Indian technology arm of KSB SE & Co. KGaA, a global industrial group with more than 150 years of history. The organization supports KSB businesses worldwide with engineering design and IT services, contributing to software, digital products, and technical innovation across multiple domains.

KSB is active in the manufacture and trade of pumps, valves, and related equipment used in water handling, chemicals, sewage, agriculture, industry, energy, buildings, and other sectors. It operates internationally through subsidiaries, supported by a wide service network with 170 service centres and over 3,000 service professionals. KSB Tech Private Limited was established in India in 2005 to help meet the group’s engineering, software, and IT development needs.

Role Summary

The company is seeking a highly motivated Lead Data Scientist to shape advanced analytics and data-driven innovation for PumpTest and IIoT-based digital platforms within the TPD Business Unit. The role focuses on building scalable analytical models, statistical methods, and data science workflows that turn large industrial and telemetry datasets into practical business insights.

You will partner with engineering, analytics, product, and business teams to deliver dependable, high-performance, and future-ready data science solutions that support predictive analytics, operational optimization, and long-term AI/ML initiatives.

What You Will Do

• Create advanced analytics and data science solutions for multiple IIoT platforms.
• Use statistical analysis, predictive modelling, and scalable algorithms to support better decision-making.
• Convert industrial and telemetry data into actionable insights for the business.
• Build scalable models and performance-focused algorithms using Python.
• Analyze large datasets using quantitative and statistical methods.
• Develop data science workflows with Python, Spark, and Databricks.
• Deliver predictive analytics and insight generation for PumpTest and IIoT solutions.
• Work closely with engineering, analytics, and product teams on use cases and architecture choices.
• Support reliable, maintainable, and efficient analytics solutions.
• Assist with data modelling, transformation, and feature engineering.
• Improve automation, monitoring, and continuous enhancement of analytics workflows.
• Build reusable frameworks and promote best practices for data science work.
• Own the quality and development of analytical models and algorithms.
• Ensure solutions remain accurate, scalable, and business-relevant.
• Support broader analytics and AI/ML platform strategy.

Requirements

• A bachelor’s or master’s degree in Mathematics, Data Science, Statistics, Computer Science, or a related discipline.
• Strong grounding in mathematical statistics and data science theory.
• Hands-on exposure to statistical analysis of large datasets.
• Strong programming skills in Python.
• Experience creating scalable and performance-sensitive algorithms.
• Practical familiarity with Python tools such as Jupyter, pandas, NumPy, SciPy, and scikit-learn.
• Exposure to Apache Spark and Databricks is preferred.
• Understanding of data pipelines, data lakes, and cloud-based analytics environments.
• Awareness of CI/CD and automation approaches in analytics workflows.
• Experience with real-time or IIoT data processing will be an added advantage.
• Disciplined and sustainable coding habits.
• Strong analytical thinking and problem-solving ability.
• Structured, accurate, and detail-focused working style.
• Self-driven attitude, willingness to learn, and a hands-on approach.
• Strong communication skills and ability to work with stakeholders.
• Comfort working in cross-functional teams.
• Very good written and spoken English.

Eligibility

Applicants should hold a B.Tech / B.E. in Computer Science and Engineering, Computer Science and Business System, Artificial Intelligence and Data Science, or Artificial Intelligence and Machine Learning.

Performance Criteria

• Accuracy and dependability of analytical models.
• Scalability and speed of data science solutions.
• Timely completion of analytics initiatives.
• Maintainability and quality of code and algorithms.
• Business impact created through insights and predictive analytics.
• Effectiveness of collaboration across teams.

Additional Information

Location: Pune, India.

This is a full-time position. No stipend or salary details were provided in the source, and the number of openings, joining timeline, and application deadline were not specified.