Data Scientist

Must-Have Skills: Extract and present valuable information from data Understand business requirements and generate insights Build mathematical models, validate and work with them Explain complex topics tailored to the audience Validate and follow up on results Work with large and complex data sets Establish priorities with clear goals and responsibilities to achieve a high level of performance. Work in an agile and iterative manner on solving problems Evaluate different options proactively and the ability to solve problems in an innovative way.

Develop new solutions or combine existing methods to create new approaches. Good understanding of Digital & analytics Strong communication skills, orally and in writing Job Overview: As a Data Scientist, you will work in collaboration with our business and engineering people, on creating value from data. Often the work requires solving complex problems by turning vast amounts of data into business insights through advanced analytics, modeling, and machine learning.

You have a strong foundation in analytics, mathematical modeling, computer science, and math - coupled with a strong business sense. You proactively fetch information from various sources and analyze it for better understanding of how the business performs. Furthermore, you model and build AI tools that automate certain processes within the company. The solutions produced will be implemented to impact business results.

The Data Scientist believes in a non-hierarchical culture of collaboration, transparency, safety, and trust. Working with a focus on value creation, growth, and serving customers with full ownership and accountability. Delivering exceptional customer and business results Industry: Any (prefer – Manufacturing, Logistics); willingness to learn manufacturing systems (OT systems and data stores) Primary Responsibilities: Develop an understanding of business obstacles, create solutions based on advanced analytics and draw implications for model development Combine, explore, and draw insights from data.

Often large and complex data assets from different parts of the business. Design and build explorative, predictive- or prescriptive models, utilizing optimization, simulation, and machine learning techniques Prototype and pilot new solutions and be a part of the aim of ‘productizing’ those valuable solutions that can have an impact at a global scale Guides and coaches other chapter colleagues to help solve data/technical problems at an operational level, and in methodologies to help improve development processes Identifies and interprets trends and patterns in complex data sets to enable the business to make data-driven decisions