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