General Manager Principal Data Scientist

Role Overview: As a General Manager Principal Data Scientist at Welspun, you will be a highly skilled and results-driven individual with expertise in predictive modeling, traditional machine learning, and Industry 4.0 analytics. Your role will involve managing a team of data scientists and analysts, leading high-impact analytics projects, collaborating with senior leadership, and contributing hands-on to critical initiatives. You will play a key role in optimizing manufacturing processes, enhancing operational efficiency, and driving digital transformation across smart factory and industrial ecosystems. Key Responsibilities: - Lead, mentor, and guide a team of data scientists, ML engineers, and analysts to deliver high-impact analytics projects - Collaborate with senior leadership and the CEO to define data science strategy and translate business challenges into data-driven opportunities - Evangelize data science best practices and ensure the adoption of scalable and efficient methodologies - Design, build, and deploy predictive and prescriptive models to address manufacturing and operational challenges such as predictive maintenance, quality optimization, and energy efficiency - Apply traditional ML techniques including regression, classification, time series forecasting, clustering, and anomaly detection - Perform model validation, optimization, and monitoring to ensure robustness and business relevance - Leverage Python, PySpark, SQL, and cloud-based data platforms (AWS, Azure, Databricks) for model development and deployment - Work with large-scale multisource industrial datasets including sensor IoT, ERP, and MES data - Collaborate with data engineering teams to design efficient data pipelines and feature stores - Translate analytical insights into actionable business recommendations and present outcomes to executive leadership - Quantify the ROI of analytics initiatives and measure their impact on KPIs such as production efficiency, downtime reduction, and quality improvement Qualification Required: - 10 years of experience in the field - Proficiency in Business & Commercial acumen, Entrepreneurship, Global Mind-set, People Excellence, Machine Learning, Python, PySpark, and Predictive Modelling (Note: Additional details about the company have been omitted as they were not included in the job description provided.) Role Overview: As a General Manager Principal Data Scientist at Welspun, you will be a highly skilled and results-driven individual with expertise in predictive modeling, traditional machine learning, and Industry 4.0 analytics. Your role will involve managing a team of data scientists and analysts, leading high-impact analytics projects, collaborating with senior leadership, and contributing hands-on to critical initiatives. You will play a key role in optimizing manufacturing processes, enhancing operational efficiency, and driving digital transformation across smart factory and industrial ecosystems. Key Responsibilities: - Lead, mentor, and guide a team of data scientists, ML engineers, and analysts to deliver high-impact analytics projects - Collaborate with senior leadership and the CEO to define data science strategy and translate business challenges into data-driven opportunities - Evangelize data science best practices and ensure the adoption of scalable and efficient methodologies - Design, build, and deploy predictive and prescriptive models to address manufacturing and operational challenges such as predictive maintenance, quality optimization, and energy efficiency - Apply traditional ML techniques including regression, classification, time series forecasting, clustering, and anomaly detection - Perform model validation, optimization, and monitoring to ensure robustness and business relevance - Leverage Python, PySpark, SQL, and cloud-based data platforms (AWS, Azure, Databricks) for model development and deployment - Work with large-scale multisource industrial datasets including sensor IoT, ERP, and MES data - Collaborate with data engineering teams to design efficient data pipelines and feature stores - Translate analytical insights into actionable business recommendations and present outcomes to executive leadership - Quantify the ROI of analytics initiatives and measure their impact on KPIs such as production efficiency, downtime reduction, and quality improvement Qualification Required: - 10 years of experience in the field - Proficiency in Business & Commercial acumen, Entrepreneurship, Global Mind-set, People Excellence, Machine Learning, Python, PySpark, and Predictive Modelling (Note: Additional details about the company have been omitted as they were not included in the job description provided.)