Data Science & AI Specialist - Industrial Analytics

ABB INDIA LIMITED
Posted on
ABB INDIA LIMITED logo

Experience
2 - 5 yrs
Job Location
Bengaluru, India
Vacancy
1
Designation
Data Science Analyst
Job Type
Not specified

Job Description

This Position reports to:
Digital Solution Engineering Manager
What we believe in
ABBs Process Automation business area enables customers to operate some of the worlds largest and most complex industrial infrastructures, helping them outrun leaner and cleaner.
We offer a broad range of automation, electrification and digital solutions for process, hybrid and maritime industries, including industry-specific integrated control and software as well as measurement and analytics solutions and services.
Your Roles and Responsibilities
In this role, we are looking for RD/Data Science/ AI Engineers with data science expertise to conceptualize, define and build industry specific digital solutions in our Process Automation Digital organization. The candidate should have a good foundation in statistics, mathematics, and machine learning. He/she will conceptualize and implement machinery and process monitoring and diagnostic digital solutions. Additionally, he/she will develop working prototypes for evaluation and customer demonstration. The candidate should leverage latest developments in AI/ML field with cross-functional industrial data and develop base algorithms for different asset performance and lifting scenarios under time-variant operating profiles.
This role is contributing to Process Automation business for Process Automation Digital division based in Bangalore Southfield, India.
You will be accountable for:
  • Develop machine learning and artificial intelligence-based solutions for process automation digital organization.
  • Utilize latest developments in industrial digitization, connected devices and systems.
  • Create scalable models and algorithms for integrating into proprietary tools and products.
  • Analyze data, understand features, evaluate alternate models, validate hypothesis through theoretical and empirical approaches.
  • Create statistical and predictive models for equipment monitoring, failure detection, life estimation and life extension. Build tools and support structures needed for analyzing data, perform data cleansing, feature selection and feature engineering.
  • Work closely with customers and Business Units (BUs) to architect and develop customer centric solutions tailored to their requirements.
  • Practice agile development of digital solution Proof of Concepts to effectively articulate the Customer Value Proposition
  • Provide industry specific domain insights for rich proposal responses by articulating customer value proposition
Qualifications for the role
  • Education- PhD / M. Tech. / MS in either Statistics/ Physics or any branch of engineering. Suitable profiles in the fields of Statistics/ Mathematics / Physics might also apply
  • 2 to 5 years of overall work experience in data science pertaining to solving industrial analytics problem statements
  • Extensive programming experience in one or more of the following languages: Python (preferred), R, Matlab, C and C++
  • Experience with deep learning frameworks like PyTorch and TensorFlow is preferred
  • Familiarity with technologies like Docker, Kubernetes and ML flow is good to have
  • Agile development of customer centric prototypes / Proof of Concepts for focused digital solutions
More about us
ABB is a leading global technology company that energizes the transformation of society and industry to achieve a more productive, sustainable future. The Process Automation (PA) business area (>$6B revenue in 2021, 22,000 employees), automates, electrifies and digitalizes some of the most complex industrial infrastructures on this planet. Through its five divisions, it serves customers in the energy, process and hybrid industries from hydrocarbons, chemicals, water, mining, minerals, pulp paper to marine and ports, and many more. PA stands at the heart of some of the most important shifts in society, helping the energy-intense industries to safer, smarter and more sustainable operations to enable a prosperous, low-carbon society.

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