DATA SCIENTIST

Stockholm
Up to 750000kr per annum

DATA SCIENTIST

BUSINESS TECHNOLOGY

STOCKHOLM

Harnham is now recruiting for a skilled Data Scientist to perform analysis on a large amount of
unstructured data. Do you have what it takes to create invaluable business insights for a major business technology provider?

THE COMPANY:


The company is a leading digital innovator, aiding businesses in serving their customers through technological solutions.

THE ROLE:


As a Data Scientist you will perform statistic analysis based on the company's business priotities. In order to create valuable insights to the business, you will perform a wide range of interdisciplinary tasks, including:

  • Data Mining
  • Data Aggregation
  • Stastical analysis
  • Developing custom algorithms
  • Machine Learning


YOUR SKILLS AND EXPERIENCE:

You must have:

  • MSc or PhD in Computer Science, Statistics or Mathematics (or similar)
  • 3-5 Years demonstrable experience in Data Science
  • Experience in programming languages (R/Python/Scala)
  • Strong communication skills


BENEFITS:

  • Innovative environment
  • Flexible hours

HOW TO APPLY:


Please register your interest by sending your CV via the Apply link on this page. For more information about similar Data Scientist positions in the Nordics, please contact Elise Myhren at Harnham.

KEYWORDS:


SPSS, SQL, Python, R, Hadoop, Spark, Data Mining, Data Science, Data Scientist, Analyse, Machine Learning
Business Technology, Technology, Scala, Big Data, Databaser, Datavisualisering, Predictive modelling, Online

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VAC-912863/EM
Stockholm
Up to 750000kr per annum
  1. Permanent
  2. Deep Learning and AI

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Visit our Blogs & News portal or check out our recent posts below.

How Computer Vision Is Streamlining Manufacturing

Since the Ford Motor Company first introduced the assembly line for car production, automation has been part of the manufacturing industry. Over 100 years later, Computer Vision adds another layer to streamlined processes. Industrial robots. Drones. Automation. With the adoption of AI technologies and its connective capabilities, we’re in the next age of Smart Manufacturing. Demand is led by supply and, as consumers demand more, manufacturers are constantly evolving to ensure their processes are efficient and safe. The implementation of machines allows them to make sure quality control measures are in place and catch issues before breakdowns occur. This verification of output far outpaces the human eye and opens up opportunities for more creative thinking.  Working Hand In (Robotic) Hand While there may still be some element of fear regarding machines taking over jobs, this isn’t the intent. Ultimately, the idea is for humans and machines to partner for more streamlined and efficient processes within the industry. The role of machines is to continue the automation of processes using image recognition, gathering insights from AI-driven Analytics solutions, and optimising operations across facilities. We continue to retain oversight of these processes, but are now also free to focus on higher-value tasks at the same time, allowing strategic and creative thinking to take the lead.  Computer Vision is playing a crucial role in the implementation of AI in manufacturing and its use is estimated to grow more than 45% by 2025. Why? Here are a few reasons: Quality inspectionPredictive maintenanceDefect reductionProductivity improvement Human-machine partnerships through the adoption of AI, cloud-based technologies, and Computer Vision are helping to prepare facilities to become networked factories. Not unlike the un-siloed Data teams working throughout a variety of industries, the factory will also link their teams. From design to supply chain, the production line to quality control; the coming years will see continued growth in the output and efficiency of today’s manufacturer. Looking Out For Bias However, there is one area in which Computer Vision remains lacking. Navigating visual images still contains within it a bias which can be detrimental to some production output use cases. Think cars, wearable devices, or uniforms. The biases and stereotypes found most often in Computer Vision algorithms are three attributes protected by anti-discrimination law; gender, skin colour, and age. To help combat these biases and make imageable visuals more easily identifiable, two computer scientists embarked upon a research project.  What they found was that not only were there biases in these areas but some visual clues still posed problems.  However, the images used to train Computer Vision technologies can determine the differences. Not just in people, but in landscape and objects as well. By crowdsourcing correct categorisations, automating image collection, and more aptly defining words to negate stereotypical phrasings, researchers are striving toward a bias-free image capture. Seeking Out Business Goals In the last few years, Computer Vision has made great strides in uniting technologies to streamline the manufacturing process. As researchers work to reduce bias in computer vision and AI, machines become ever more essential for meeting business goals. Factories with smart manufacturing systems can more quickly process inefficiencies with improved accuracy. In 2017, sales of Computer Vision and automation systems grew 14.6% over the previous year to $2.633 billion. All industries are noticing the benefits of Computer Vision as an essential system but, like the Ford Motor Company in the early 20th century, manufacturing looks once again set to lead the world in innovation.  Ready to take the next step in your career? Whether you’re interested in AI, Big Data and Analytics, Computer Vision or more, we may have a role for you. Check out our current vacancies or get in touch with one of our expert consultants to find out more.  

What Does The Fourth Industrial Revolution Look Like?

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