Procter & Gamble Hiring for PS Manager- Hub Site Data Scientist at Bhopal, Madhya Pradesh Full Time

P&G was founded over 180 years ago as a simple soap and candle company. Today, we’re the world’s largest consumer goods company and home to iconic, trusted brands that make life a little bit easier in small but meaningful ways. We’ve spanned three centuries thanks to three simple ideas: leadership, innovation and citizenship. The insight, innovation and passion of hardworking teams has helped us grow into a global company that is governed responsibly and ethically, that is open and transparent, and that supports good causes and protects the environment. This is a place where you can be proud to work and do something that matters.

Dedication from Us:
You’ll be at the core of breakthrough innovations, be given exciting assignments, lead initiatives, and take ownership and responsibility, in creative work spaces where new ideas flourish. All the while, you’ll receive outstanding training to help you become a leader in your field. It is not just about what you’ll do, but how you’ll feel: encouraged, valued, purposeful, challenged, heard, and inspired.

What we Offer:
Continuous mentorship – you will collaborate with passionate peers and receive both formal training as well as day-to-day mentoring from your manager dynamic and supportive work environment- employees are at the centre, we value every individual and support initiatives, promoting agility and work/life balance.

Just so you know:
We are an equal opportunity employer and value diversity at our company. Our mission of diversity and inclusion is: “Everyone valued. Everyone included. Everyone performing at their peak”.

Role Responsibilities:
You will provide technical leadership in supporting OU innovation projects and act as a key enabler in leading and delivering results against challenges. You will work with the innovation team looking at new platforms, machine control, data processing and analytics. You will also:

Develop and plan required analytic projects in response to business needs. Leverage data science tools to solve the toughest process problems in the region.

Develop new analytics/predictive/prescriptive modeling methods and/or tools as required. Propose prescriptive analytic models to build robust and fault-tolerant process control strategies to reduce Operations Effort and improve product quality

Work with process/equipment experts and application developers to identify data relevant for analysis.

Contribute together with process/equipment owners and ITOT to the development and evolution of data models for analytical capabilities. Own data model and maintenance and development for hub-site

Develop and maintain data pipelines for the hub-site

Contribute to define work processes to deploy and maintain predictive/analytical modeling architectures, modeling standards, alarming and reporting, and data analysis methodologies.

Conduct external focus research to drive suggestions on analytical modeling products, services, protocols, and standards that might support and speed-up the smart manufacturing journey.

Identify, diagnose, and resolve prognostics model performance issue. Leverage Reliability Engineering enhance with data science to develop new solutions to reduce losses.

Qualifications

Sufficient business knowledge to understand what data is important, when findings are relevant, and how to exploit data to make decisions.

Strong familiarity with data preparation and processing.

Strong analytical statistical and mathematical modeling capabilities to form hypothesis and to collect, explore, and extract insights from structure and unstructured data to rationally transform raw data into useful information to improve process/equipment operation and maintenance.

Efficient use of software for data visualization, statistical analysis and ML, e.g., Python, R, SAS, Azure ML, Matlab, PowerBi, Tableau, and familiarity with functional programming and scripting languages, e.g., .NET, VB, C++, Python, Matlab.

Understanding data architecture concepts, i.e., relational database structures, data warehouse, big data management, data queries, etc.

Technical understanding of mechatronic systems / first principles (combining principles of process, mechanic, electrical, control and systems engineering)

Teamwork attitude with clear technical communication