Technical Lead - Data Scientist

Tech Lead - Data Scientist

Purpose of the Role

·        Design and develop advanced data science and analytics solutions for various IIOT platforms

·        Enable data-driven decision-making through statistical analysis, predictive models, and scalable analytical algorithms

·        Transform large-scale industrial and telemetry data into actionable business insights

·        Support long-term AI/ML and analytics strategy within TPD digital initiatives

Key Tasks & Activities

·        Develop scalable analytical models and performance-critical algorithms using Python

·        Perform quantitative statistical analysis on large-scale industrial and telemetry datasets

·        Design and implement data science workflows using Python, Spark, and Databricks

·        Build predictive analytics and data-driven insights for PumpTest and IIoT solutions

·        Collaborate with engineering, analytics, and product teams on data-driven use cases

·        Contribute to architecture decisions for analytics and data science platforms

·        Ensure reliability, maintainability, and performance of analytical solutions

·        Support data modeling, transformation, and feature engineering processes

·        Drive automation, monitoring, and continuous improvement of analytical workflows

·        Contribute to reusable frameworks and best practices for data science initiatives

Accountability

·        Own development and quality of analytical models and algorithms

·        Ensure scalability and accuracy of data science solutions

·        Support business decision-making through reliable insights and predictive analytics

·        Drive alignment between business needs and data-driven solutions

·        Contribute to long-term analytics and AI/ML platform strategy

Technical / Professional Requirements

·        Bachelor’s or Master’s degree in Mathematics, Data Science, Statistics, Computer Science, or related field

·        Strong theoretical knowledge in mathematical statistics and data science

·        Practical experience in quantitative statistical analysis of large datasets

·        Strong programming expertise in Python

·        Experience developing scalable and performance-critical algorithms

·        Hands-on experience with Python ecosystem tools: Jupyter, pandas, NumPy, SciPy, scikit-learn

·        Experience with Apache Spark and Databricks is preferred

·        Understanding of data pipelines, data lakes, and cloud-based analytics platforms

·        Familiarity with CI/CD and automation practices in analytics workflows

·        Knowledge of real-time or IIoT data processing is an advantage

Personal Competencies

·        Disciplined and sustainable coding practices

·        Strong analytical and problem-solving skills

·        Precise, structured, and detail-oriented working style

·        Self-motivated with strong learning agility and hands-on mentality

·        Strong communication and stakeholder collaboration skills

·        Team-oriented mindset and ability to work cross-functionally

·        Very good English communication skills (written and spoken)

Performance Criteria

·        Accuracy and reliability of analytical models

·        Scalability and performance of data science solutions

·        Timely delivery of analytics initiatives

·        Quality and maintainability of code and algorithms

·        Business value generated through insights and predictive analytics

·        Collaboration effectiveness across teams

Experience Level

Senior Level