Job Description
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