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Data Scientist

Zmluva na dobu neurčitú
Paris
Plat: Neuvedené
Žiadna práca na diaľku
Vzdelanie: Magisterský stupeň vzdelania

Numberly
Numberly

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Pozícia

Popis pracovnej ponuky

We are looking for a data scientist to work on innovative projects in the field of digital marketing.

Your job will be to help our team optimize Digital Marketing campaigns using Applied Mathematics and Machine Learning. You will join the data science and analysis team, composed of data scientists, data analysts and a machine learning engineer, where you will be designing new algorithms using your knowledge and analytical skills in order to take on new business challenges. 

Position summary:

  • You will take part in the elaboration, optimization and development of machine-learning algorithms, to improve the efficiency of Numberly’s Relationship Marketing Programs (examples of projects we are currently working on include: scoring of users with their probability of purchase, ranking inventories according to their predicted performance, product recommendation algorithm, reinforcement learning applied to banner selection ...)

  • You will have the ownership of the new algorithms you build, from understanding and assessing the business need to the modelisation (based on literature reviews) and finally the implementation in production with the help of our data engineers and machine learning engineer.

  • You will work closely with marketing teams, project managers, data engineers and machine learning engineers and developers 

  • You will help improve existing algorithms, add new features and adapt them to a complex and always changing environment

  • You will have access to large datasets to build supervised or unsupervised algorithms:

  • behavioral and declarative data collected in real time

  • thousands of socio-demographic variables on millions of individuals

  • transactional data collected by our clients

  • At Numberly, we share a passion for transmission: weekly seminars, talks with professionals who are experts in their field, permanent learning.
  • A fast and powerful onboarding, thanks in particular to :
  • Jedi Masters given to new recruits;
  • Live my life in different teams;
  • Happy Meetings attended by all the teams in the world to share the group's news.
  • We cultivate the freedom of speech that allows everyone to participate in the group's influence. Through 1000mercis impacts but also through our activities that create value in the open Internet, we have a positive impact on our ecosystem.
  • Numberly is Gender Equal by design (gender equality index of 97/100 in 2020, WeConnect International certification).
  • Numberly is an international environment (you interact with many nationalities on a daily basis) where you feel at home: warm offices, friendly kitchens, a precise library, space for bicycles. Coffee and tea at your disposal. Mystery lunches, fancy dress parties and sports classes.
  • Possibility to be in remote up to 50% of your time (to be arranged as you wish) and to work up to 60 consecutive days (working) in remote.
  • Swile card (meal vouchers).
  • Numberly welcomes candidates with disabilities.

Preferované skúsenosti

  • Master's degree required in a quantitative field such as Machine learning, Statistics or Applied Mathematics or a generic master such as engineering with a specialization in a quantitative discipline

  • Machine learning algorithms knowledge (both supervised and unsupervised) is required

  • Coding skills in an object oriented language is required (Python prefered, Java, Scala …)

  • SQL knowledge will be strongly appreciated

  • Knowledge or experience in Spark and airflow is a plus

  • Highly motivated, intellectually curious, strongly interested in the digital industry

  • Start-up spirit, capable at multitasking and prioritizing workload  

  • Excellent communication skills, strong motivation to work in a fast growing company in an international environment

Technical environment in Numberly:

  • Hadoop ecosystem  (HDFS, Hive ... )

  • Apache Spark

  • Apache Airflow

  • SQL Databases (Postgres, SQLServer)

  • NoSQL databases (MongoDB, ScyllaDB, ElasticSearch, ...) and graph database (Neo4j)

  • Apache Kafka

  • Python, Java, Scala

  • Git, Linux

  • Docker, Kubernetes

  • FastAPI

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