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About this job
Compensation: €45k - 65k
Location options: Paid relocation
Job type: Full-time
Experience level: Senior, Lead
Role: Data Scientist
Industry: CNC Machining, Industrial Automation, Manufacturing
Company size: 10k+ people
Company type: Public
Technologies
r, machine-learning, python, deep-learning, bigdata
Job description
Job description
CODE
Do you have a passion for data science & engineering? We do. And we have all the means to do an excellent job: access to any technology stack, world-class experts and a great team.
We are looking for a Data Scientist, to join us in building our portfolio of services and products; aiming to transform the manufacturing industry. This position is located in our brand-new office at Regeringsgatan, in the heart of Stockholm.
Job Summary
In this role, you play a vital part in developing our tech stack by combining your interest for new technology with a passion for solving hard manufacturing problems. You are part of our data science organization, with the mission to turn proof-of-concepts and ideas into production-ready features for consumption by our broader digital services portfolio.
Your responsibilities
- Working closely with our executives, product managers, engineers and designers to identify and map out the most purposeful use cases for data science and artificial intelligence inside Sandvik Machining Solutions.
- Working with Sandvik’s engineering teams to design and develop conceptual models and derive best practices from integration of data science into existing and new products and services.
- Prototyping, validating and iterating data science-driven use cases across strategic focus areas within the Group, including additive manufacturing, metal cutting, logistics and planning and cross-team collaboration.
- Helping junior team members.
Concrete examples from a life of a Data Scientist @ CODE:
- Finding anomalies in a live data stream from a large array of sensors that monitor an industrial process. Looking at vast amount of collected data, you search for ways to improve quality and increase productivity.
- A skilled operator can hear if milling is not going as it should. Can you make a model that will tell the user if the process is not going well?
- Mining the internet in search for relevant information on manufacturing and turning it into a data product. What patterns emerge when we aggregate the data? What new information do we have on our customers?
Your skills and qualifications
Data Science is a vast and multidisciplinary field. We are looking for people with extensive knowledge in one of the following areas:
- Machine learning
- Time series analysis
- Statistics, applied mathematics or computational physics
- Cloud computing and building data products
- Supply chain, manufacturing and other relevant domains
Other required skills
- At least four years of experience in designing, building and deploying data science solutions in a professional environment
- Python. R if time series analysis is your domain
- Visualization of (large) data sets
- SQL or NoSQL
- Great communication skills in English, both verbal and written
- Experience in leading projects and / or people
Bonus skills and qualifications
- R, Scala or similar language
- GCP, AWS, Azure or equivalent
- js, dygraphs or equivalent
- Apache Spark or other distributed programming framework
- Graph databases (e.g. Neo4j)
- Containers and container-orchestration systems (e.g. Docker & Kubernetes)
- Scientific papers in peer-reviewed journals
We are a company with an open-minded culture, actively working to create a workplace that is characterized by diversity and inclusion.
Showcase your skills!
Since we’d love to get to know you better as a data scientist, please showcase your skills by adding your StackOverflow profile, GitHub username, ORCID or equivalent in your application.
Questions?
Please shoot them to Lukasz Tracewski, hiring manager: [email protected]
Hur du söker jobbet
Notera att denna annons är publicerad via en av våra partners, där särskilda vilkor (krav på medlemskap, separat ansökning eller liknande) kan tillämpas.