ML Engineer

1 month ago

Chennai, India timesjobs Full time

Vestas is the world leader in wind technology and a driving-force in the development of the wind power industry. Vestas' core business comprises the development, manufacture, sale, marketing, and maintenance of Wind Turbines. Come and join us at Vestas

Digital Business Transformation > Service Analytics > Analytics Development

Analytics Development team is part of Service Analytics-Digital Solutions, the data insights center of excellence (CoE) for the Service organization at Vestas. This team is responsible for creating data products using the latest technology, that create value by solving business requirements or risks, in coordination with Product Managers, Product Owners and Scrum Masters, also part of the Service Analytics organization. The data products are crucial for the Service business unit, a 10k people organization that relies on these data insights for data-focussed decision-making and performance management.

Responsibilities

Primary duties will be to develop, test and deploy statistical and machine learning models for advanced analytics use cases in service operations area
Support Data Scientists in feasibility studies and rapid experimentation to build ML prototypes to validate & assess potential impact, usefulness, complexity, and benefits of new ideas
Develop, productionize, and deploy scalable ML solutions with automated drift monitoring from approved ML prototypes
Responsible for packaging ML solutions for end-user consumption, including building API endpoints, web applications and end user interfaces
Collaborate with data engineers to build scalable data pipelines to support ML deployments
Share knowledge and be an active consultant to explain and showcase potentials of data science driven use-cases and industrializing machine learning in Vestas Service

Qualifications

Background in Engineering / Applied Statistics at Bachelors (Degree in Computer Science, IT, Business Science, Engineering or similar)
Masters in Analytics/Data Science, certificate courses from recognized institutions an added advantage
Relevant experience in advanced data analytics, statistical modeling, and data science
Has been working as a ML Engineer for 2 years, with an overall experience in data & analytics of 4-6 years

Competencies

Bring not just an analytics-orientation, but the ability to use analytics to drive key success metrics related to yield management and revenue generation
Experienced on the commercial side, and decidedly "hands-on" and not just theoretical
Familiar with business metrics such as KPIs and other indicators
Pro-active, curious, structured, self-motivated, reliable, credible, open minded, ambitious
Fluency in English and have good communication, presentation skills

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