Data Science & AI Specialist

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:

• 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.
• Conceptualize and develop process control and scheduling algorithms in the domain of industrial analytics.
• Solutionize optimization algorithms and their output visualizations by packaging them as industrial business value apps.
• 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.