Tech Lead - Ds

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