Senior Data Scientist

3 weeks ago

Bjerringbro, Denmark GRUNDFOS Full time

What is the job about?

Are you excited about leveraging machine learning and advanced statistical methods to facilitate innovation? As a Senior Data Scientist at Grundfos, you will engage in projects that leverage artificial intelligence and machine learning to develop innovative solutions for our digital offerings, which aim at enhancing water system monitoring, improving energy efficiency in pump systems, detecting irregularities within IoT frameworks, and enabling foresight in maintenance schedules. You'll join a collaborative team of Data Scientists and Data Engineers in our AI Solutions department, contributing to the company's digital transformation agenda.

Your main responsibilities:

Lead machine learning and advanced statistical projects to deliver actionable insights and AI/ML features for our digital products. Participate in both the development and deployment phases of data science processes, integrated with our Data and AI platforms. Propose, scope, and formulate data-driven projects that align with business objectives, maintaining key stakeholder relationships. Engage with stakeholders to communicate project ideas and gather feedback for AI/ML solutions, ensuring successful collaborations across different business sectors. Apply real-time control techniques and documented understanding of the water domain to create impactful solutions. Stay current with the latest trends and advancements in Data Science to enhance the quality of projects, contributing to the broader AI/ML strategy of Grundfos.

Your background:

We imagine that you have:

Degree in data science, statistics, computer science, or similar. A background in water engineering with documented AI skills is also highly valued. 4+ years of experience in similar role. Proficiency in Python and R, with solid software development skills. Experience with working in a cloud-based environment. Extensive experience in statistical and mathematical modeling, including time series analysis and machine learning. Familiarity with data management tools like SQL. Practical experience with MLOps and deployment technologies both on edge and cloud.