Frankfurt am Main, Hessen
€75000 - €85000 per annum

75.000 - 85.000€
Frankfurt und Umgebung, Germany

Senior Data Scientist Position in einer Unternehmensberatung mit Start-Up Mentalität

Bei dieser Position handelt es sich um die perfekte Möglichkeit deine Projekt- und Data Science-Erfahrung zu nutzen, um andere Unternehmen fit für zukünftige Herausforderungen zu machen, während du selbst deine eigene Karriere vorantreibst.


Dieses Beratungsunternehmen bietet die Agilität eines Start-Ups und die Erfahrung eines gestandenen Unternehmens. Und mit Hilfe der Nutzung der neuesten Data Science Methoden trägt es maßgeblich dazu bei, dass andere Unternehmen erfolgreich aus dem derzeitigen digitalen Umbruch hervorgehen und gestärkt an zukünftige Herausforderungen herantreten können.


In deiner Rolle als Senior Data Scientist wirst du mit Hilfe der neuesten Technologien und deinem Projektverständnis andere Unternehmen dazu befähigen, selbstverantwortlich bessere Analysen und Entscheidungen zu treffen. In diesem Zusammenhang wirst du folgende Aufgaben übernehmen:

  • Die Nutzung von Machine Learning Methoden, um die anfallenden Daten auf- und weiterzuverarbeiten, sowie Datenanalysen durchzuführen
  • Die Automatisierung von Data Mining-Prozessen, basierend auf individuellen Anforderungen der Kunden
  • Fortschrittliche Herangehensweisen nutzen, um die Problemstellung der Kunden zu lösen
  • Die Implementierung von erarbeiteten Lösungen beim Kunden


  • Master oder PhD in einem relevanten MINT-Fach
  • Umfangreiches (Anwendungs-)Wissen in Statistik, Maschinelles Lernen, Datenvisualisierung und Advanced Analytics
  • Gewandter Umgang mit SQL
  • Ausgeprägte, kommerzielle Erfahrung im Umgang mit Python oder R
  • Großes Interesse am selbstständigen Arbeiten und der kundenindividuellen Lösungsfindung
  • Ein hohes Maß an Motivation und Engagement
  • Erste kommerzielle oder wissenschaftliche Erfahrung in der Anwendung mit Data Science


  • Raum zur Entwicklung und Anwendung von eigenen Ideen
  • Flexible Arbeitszeiten für eine positive Work-Life-Balance
  • Kontinuierliches Verbesserungspotential, um deine Karriere einen Schritt weiter zu bringen
  • Ein professionelles Team mit kompetenten und erfahrenen Kollegen


Klingt das interessant für dich? Dann bewirb dich direkt hier über die Website und sende deinen CV an Tim Schröder.

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Frankfurt am Main, Hessen
€75000 - €85000 per annum
  1. Permanent
  2. Data science

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Harnham blog & news

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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?

We’re in the next stage of the fourth Industrial Revolution and technologies continue to merge. No longer is advancement as simple as adding “tech” to the end of a word - sorry Fintech, InsurTech, HRTech, and the rest. Now technologies stand together as each becomes a separate piece of how tech operates in the business world. AI and IoT have merged to become AIoT. Data is as much commodity as it is information to fuel business growth. Computer Vision partnered with AI is teaching computers to convert their ones and zeros to images humans take for granted.   In a word, it’s a transformative time for every industry and every industry is taking advantage of the benefits in one way or another. Smart manufacturing. Human Resources. Marketing. Even insurance has joined the party. But, with so many advancements, we thought we’d take a look at just the tip of the iceberg, starting with A, B, and C.  AI Meets IoT  We’ve all heard how AI and the Internet of Things (wearable and smart devices etc.) are being used in the Health sector. With the kind of real-time Data available, patients, insurers, and medical professionals can map out health plans based on wearable devices to track patient health and encourage preventative care.  Indeed, one insurance company is embracing these Data trends to ramp up the speed and efficiency of their data. Using Machine Learning and IoT sensors to develop an AI-based solution, customer information is used to match clients with the right policies tailored to their needs.  Car insurance is another industry to benefit. Insurers are able to collect real-time driving data which they can analyse to determine risk or offer discounted policies for good driving. This kind of information can also be used to revisit and reconstruct accident scenes to figure out what happened and who’s at fault.  Big Data, Big Money We’ve all heard the phrase ‘Data Is The New Oil’ by now, which I’m sure we can all agree, just means Data is a resource everybody wants and is willing to pay a lot for. But the differences between Data and Oil are two-fold; Data has the potential to be infinite, and it tells us about what oil cannot; the human experience.  Cloud technologies, edge hardware, and the IoT have helped shape the digitisation of objects, people, and organisations. From sensors to wearable devices, more and more data is being collected, allowing us to be more connected than ever before. It’s also providing more information to the tech giants than ever before. For example, Amazon’s Ring doorbell is logging every motion around it and can pinpoint the time to millisecond.   Add these technologies to Natural Language Processing (NLP) and watch the world around us draw value from and understand our Data like never before. The wave of Big Data value shows no signs of slowing down. Computer Vision in Business In the last few years, Computer Vision has been making great strides in the business world. Yet the Data required for processing power and memory can still be impacted by image quality. The opportunities  are alive with possibility and, from small businesses to enterprise solutions, Computer Vision has seen a variety of industries finding practical business uses.  Below are just a few additional areas Computer Vision is making its mark. Facial Recognition – providing surveillance and security systems in such areas as police work, payment portals, and retail stores.Digital Marketing – sorting and analysing online images to target ad campaigns to the right audiences.Financial Institutions –preventing fraud, allowing mobile deposits, analysing handwriting, and beyond. With the global market for fourth industry technologies predicted to be between $17.4 billion and $48.32 billion by 2023, now is the time to find your focus within the industry.  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. Take a look at our current opportunities or get in touch with one of our expert consultants to find out more.  

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