Solution Architect- Data Scientist

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

• · Bachelors or Masters 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