Job Purpose/ Summary
We are seeking a highly skilled and results-driven Principal Data Scientist with deep expertise in predictive modeling, traditional machine learning, and Industry 4.0 analytics. The ideal candidate will combine strong technical acumen with leadership capabilities, managing a team of data scientists and analysts while also contributing hands-on to critical projects.
You will be responsible for conceptualizing and delivering advanced analytics solutions to optimize manufacturing processes, enhance operational efficiency, and drive digital transformation initiatives across smart factory and industrial ecosystems.
This role involves close collaboration with CXO leadership, including the CEO, and cross-functional teams in engineering, operations, and IT to embed data-driven intelligence into business decision-making.
Job Title : General Manager Principal Data Scientist
Job Description
We are seeking a highly skilled and results-driven Principal Data Scientist with deep expertise in predictive modeling, traditional machine learning, and Industry 4.0 analytics. The ideal candidate will combine strong technical acumen with leadership capabilities, managing a team of data scientists and analysts while also contributing hands-on to critical projects.
Principal Accountabilities
- Lead mentor and guide a team of data scientists ML engineers and analysts to deliver highimpact analytics projects
- Collaborate with senior leadership and the CEO to define data science strategy and translate business challenges into datadriven 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 cloudbased data platforms AWS Azure Databricks for model development and deployment
- Work with largescale 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
(ref:hirist.tech)
