At ABB, we help industries run leaner and cleaner—and every person here makes that happen. You’ll be empowered to lead, supported to grow, and proud of the impact we create together. Join us and help run what runs the world.
This Position reports to:
Digital Solution Engineering Manager
What we believe in
ABB’s Process Automation business area enables customers to operate some of the world’s 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 role and responsibilities
We are looking for data scientists with expertise to conceptualize, define and build industry specific digital solutions in our Automation Digital organization. The candidate should have a good foundation in statistic, machine learning and optimization theory and practice. He/she will develop machine learning models to define operation of industrial assets and manufacturing processes. He/she will also conceptualize and implement algorithms to solve process optimization and scheduling problem statements. He/she should be able to leverage not only open-source optimizers present in packages like SciPy Optimize, Google OR-Tools but also commercial optimizers like IBM CPLEX and Gurobi.
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 health, process control and schedule optimization under time-variant operating profiles. The candidate is also expected to be familiar with solving various type of optimization problems like multi-objective optimization, Mixed Integer Linear / Nonlinear Programming, Quadratic Programming, Traveling Salesman Problem, Combinatorial Optimization, Constraint Programming, and Global Optimization. Exposure to meta-heuristic algorithms will add an edge to the profile.
You will be mainly accountable for:
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Create scalable models and algorithms for integrating into proprietary tools and products.
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Analyze data, understand features, evaluate alternate models, validate hypothesis through theoretical and empirical approaches.
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Create statistical and predictive models for equipment monitoring, failure detection, life estimation and life extension.
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Conceptualize and develop process control and scheduling algorithms in the domain of industrial analytics.
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Solutionize optimization algorithms and their output visualizations by packaging them as industrial business value apps.
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Work closely with customers and Business Units (BUs) to architect and develop customer centric solutions tailored to their requirements.
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Practice agile development of digital solution ‘Proof of Concepts’ to effectively articulate the Customer Value Proposition.
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Provide industry specific domain insights for rich proposal responses by articulating customer value proposition.
Location: Bengaluru, India
Qualifications for the role
Experience
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4 to 8 years of overall work experience in development of optimization workflows applied to industrial analytics
Academic
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PhD / M. Tech. / MS in either Statistics/ Operations Research/ Chemical/ Mechanical/ Electrical/ Aerospace Engineering
Technology
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Extensive programming experience in one or more of the following languages: Python (preferred), R and Matlab.
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Experience with deep learning frameworks like PyTorch and TensorFlow is preferred.
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Familiarity with technologies like Docker, Kubernetes and MLflow is good to have.
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Experience in using standard optimization solvers like SciPy Optimize, Google OR-Tools and Matlab® Optimization toolbox.
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Agile development of customer centric prototypes / ‘Proof of Concepts’ for focused digital solutions.
Domain
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Experience in development of optimization routines for process industries like petrochemicals, manufacturing, utilities etc.
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Familiarity with industrial equipment like multistage pumps and/or compressor, turbines, turbochargers, mechanical seals etc.
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Familiarity with control systems theory – state space formulations & Model Predictive Control.
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A deep understanding of optimization problem statements.
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Exposure to component/system modeling software platforms like Modelica and Simulink®.
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Beginner’s experience in software applications like MS Office will be considered an added advantage.
Soft Skills
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Strong oral and written communication skills in English.
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Ability to interact with business and operation heads to articulate business value.
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.
Building a cleaner, smarter future takes all kinds of minds: the curious, the courageous, and the creative. We welcome people from all backgrounds and experiences.
Ready to make an impact? Apply today or visit www.abb.com to learn more about the impact of our solutions across the globe.
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