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Rockwool

Senior Data Scientist

Fuldtid

Permanent

Hovedgaden 584, 2640 Hedehusene, Danmark

SE PÅ KORT
ID: 2599250
|
Indrykket for 13 dage siden

We are looking for a Senior Data Scientist to join our Data Science Team in ROCKWOOL HQ in Hedehusene. In this job, you can expect to travel about 10% of the time in support of global projects. 

Ready to help build a better future for generations to come?

In an ever-changing, fast paced world, we owe it to ourselves and our future generations to live life responsibly. At ROCKWOOL, we work relentlessly to enrich modern living through our innovative stone wool solutions. We are proud to be ranked by the prestigious Corporate Knights Inc. as the world’s most sustainable building material company in 2023.

Your future team

We have recently started a journey towards using more digitalization and automation and better use of data – and this is where your abilities come into play. As our new Senior Data Scientist, you will join our Data Science team and work at the forefront of machine learning and artificial intelligence.

What you will be doing

As our new Senior Data Scientist with expertise in computer vision and manufacturing sensor data, you will be responsible for developing advanced data models and algorithms that can be applied to real-world manufacturing data sets. The primary focus is to leverage data to drive innovation, optimize operations, and improve quality control in our products and manufacturing processes. 

In addition, we are also initiating our journey towards leveraging advanced analytics for data driven decision making in Marketing and Sales domain. We anticipate that our coming Senior Data Scientist also make vital contributions towards this initiative.

Mathematical modelling and algorithm development

  • Develop and apply models to manufacturing sensor data, including image recognition and computer vision techniques, to enhance quality control and productivity in our manufacturing process

  • Conduct experiments to validate and improve the accuracy and effectiveness of models

  • Machine Learning processes and Best Practices

  • Develop and maintain best practices and standards for carrying out Data Science projects

  • Implement Machine Learning Ops practices to streamline the development, deployment, and maintenance of models in production

  • Collaboration with the team in identifying areas for improvement and recommend strategies to enhance the data science function in our organization

  • Collaboration and stakeholder management

  • Work with process engineers to understand the data generated by sensors and translate that into actionable insights

  • Collaborate with Data engineers to identify data sources and develop efficient data pipeline strategies

  • Collaborate with colleagues from the business in establishing metrics to measure the effectiveness in the factories

  • Aid your team colleagues to extend their services into more domains such as Marketing and Sales

  • Learning and skill development

  • Stay up to date with the latest developments in Data Science to ensure that our practices are cutting-edge

  • What you bring

  • Educational background as PhD or Master's in Computer Science, Mathematics, Statistics, or related field

  • 5+ years of experience in Data Science and it would be great if you have experience with the manufacturing industry

  • Noteworthy experience in computer vision and image recognition techniques, such as OpenCV, TensorFlow, Keras, PyTorch, or scikit-image

  • You have already experience working with manufacturing sensor data, including signal processing and time-series analysis

  • Excellent skills within Python, R, SQL, and cloud computing technologies

  • Hands on experience in deploying models and algorithms into production systems is desirable

  • Experience with Machine Learning Ops tools and frameworks such as Kubeflow, MLflow, etc is desirable

  • Professional in English language

  • As a person you are curious and solution oriented. You can easily communicate complex content across functions and to non-technical colleagues. And you have a structured way of working forward, and take pride in delivering high quality output.

    We are keen to help employees develop their talents and move forward in their careers. You can expect to be supported in your professional ambitions through our programs, to help you reach your professional goals.

    Ready to apply?

    If you want to know more, please contact Director, Jack Leslie Myrup, .

    Please submit your Resumé and Cover Letter in English, the latest Sunday June 2nd, 2024.

    Who we are

    We are the world leader in stone wool solutions. Founded in 1937 in Denmark, we transform volcanic rock into safe, sustainable products that help people and communities thrive. We are a global company with more than 12,000 employees, located in 40+ countries with 51 manufacturing facilities… all focused on one common purpose – to release the natural power of stone to enrich modern living.

    Sustainability is central to our business strategy. ROCKWOOL was one of the first companies to commit to actively contributing to the United Nations Sustainable Development Goals (SDG’s) framework and are actively committed to 11 SDGs, including SDG 14, Life Below Water. Through our partnership with the One Ocean Foundation and in connection with our sponsorship of the Denmark SailGP team, we will help raise awareness around ocean health challenges in an effort to accelerate solutions to protect it.

    Diverse and Inclusive Culture

    We want all our people to feel valued, respected, included and heard. We employ 79 different nationalities worldwide and are committed to providing equal opportunities to all employees, promote diversity, and work against all forms of discrimination among ROCKWOOL employees.

    At ROCKWOOL, you will experience a friendly team environment. Our culture is very important to us. In fact, we refer to our culture as “ The ROCKWOOL Way ”. This is the foundation in which we operate and is based upon our values of ambition, responsibility, integrity and efficiency.

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