DATA SCIENTIST - Spanish Speaker

Paris, Île-de-France
€40000 - €60000 per annum

Data Scientist - Spanish Speaking
Paris, France
45000K€-60000€

While finishing up a big round of funding, this InsurTech start up is already making big moves within the European insurance world. Data is at the heart of their SaaS platform and they are growing their Data Science team with new brilliant scientists. Work language is English and Spanish (and French is always a plus living in Paris, but not required).

THE ROLE:

  • Solid knowledge in algorithm coding and programming
  • Designing and developing solutions around Machine Learning and Artificial Intelligence
  • You will be joining a team of 5 data scientists
  • You will have an occasional direct contact with the clients of the company to assess, understand, and implement your work
  • You will be working closely and tailoring your technical work to the needs of the companies in order to launch new features and functionalities to the platform

YOUR PROFILE:

  • Master's or Engineering Degree in Applied Mathematics, or other similar quantitative fields
  • Ideally a first experience in data science and machine learning
  • Good knowledge of Python, and Java / C
  • You are ambitious and passionate about your job
  • Fluent in English and another language


WHY SHOULD YOU APPLY?

  • Expending startup
  • The company develops state of the art algorithms
  • Joining a start up at the right time ! They are just starting to scale up!


HOW TO APPLY?

Please register your interest by sending your CV via the Apply link on this page.

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27482/WT
Paris, Île-de-France
€40000 - €60000 per annum
  1. Permanent
  2. Data science

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‘Tis The Season Of Data: Black Friday Is Here

‘Tis The Season Of Data: Black Friday Is Here

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How Big Data Is Impacting Logistics

How Big Data is Impacting Logistics

As Big Data can reveal patterns, trends and associations relating to human behaviour and interactions, it’s no surprise that Data & Analytics are changing the way that the supply chain sector operates today.  From informing and predicting buying trends to streamlining order processing and logistics, technological innovations are impacting the industry, boosting efficiency and improving supply chain management.  Analysing behavioural patterns Using pattern recognition systems, Artificial Intelligence is able to analyse Big Data. During this process, Artificial Intelligence defines and identifies external influences which may affect the process of operations (such as customer purchasing choices) using Machine Learning algorithms. From the Data collected, Artificial Intelligence is able to determine information or characteristics which can inform us of repetitive behaviour or predict statistically probable actions.  Consequently, organisation and planning can be undertaken with ease to improve the efficiency of the supply chain. For example, ordering a calculated amount of stock in preparation for a busy season can be made using much more accurate predictions - contributing to less over-stocking and potentially more profit. As a result, analysing behavioural patterns facilitates better management and administration, with a knock-on effect for improving processes.  Streamlining operations  Using image recognition technology, Artificial Intelligence enables quicker processes that are ideally suited for warehouses and stock control applications. Additionally, transcribing voice to text applications mean stock can be identified and processed quickly to reach its destination, reducing the human resource time required and minimising human error.  Artificial intelligence has also changed the way we use our inventory systems. Using natural language interaction, enterprises have the capability to generate reports on sales, meaning businesses can quickly identify stock concerns and replenish accordingly. Intelligence can even communicate these reports, so Data reliably reaches the next person in the supply chain, expanding capabilities for efficient operations to a level that humans physically cannot attain. It’s no surprise that when it comes to warehousing and packaging operations Artificial Intelligence can revolutionise the efficiency of current systems. With image recognition now capable of detecting which brands and logos are visible on cardboard boxes of all sizes, monitoring shelf space is now possible on a real-time basis. In turn, Artificial Intelligence is able to offer short term insights that would have previously been restricted to broad annual time frames for consumers and management alike.  Forecasting  Many companies manually undertake forecasting predictions using excel spreadsheets that are then subject to communication and data from other departments. Using this method, there’s ample room for human error as forecasting cannot be uniform across all regions in national or global companies. This can create impactful mistakes which have the potential to make predictions increasingly inaccurate.  Using intelligent stock management systems, Machine Learning algorithms can predict when stock replenishment will be required in warehouse environments. When combined with trend prediction technology, warehouses will effectively be capable enough to almost run themselves  negating the risk of human error and wasted time. Automating the forecasting process decreases cycle time, while providing early warning signals for unexpected issues, leaving businesses better prepared for most eventualities that may not have been spotted by the human eye.  Big Data is continuing to transform the world of logistics, and utilising it in the best way possible is essential to meeting customer demands and exercising agile supply chain management.  If you’re interested in utilising Artificial Intelligence and Machine Learning to help improve processes, Harnham may be able to help. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more.  Author Bio: Alex Jones is a content creator for Kendon Packaging. Now one of Britain's leading packaging companies, Kendon Packaging has been supporting businesses nationwide since the 1930s.

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