Tech Lead - Data Scientist
Skills
About the role
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
Questions about this role
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