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
