Tech Lead - Data Scientist

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