Senior Data Scientist/Tech Lead

  • Annual gross salary : from 55 K€ + benefits (negotiable depending on the profile and experience).
  • Location : Bordeaux

Your future assignments at sense4data

Lead Data Scientist in charge of several projects related to Data Science and Data Valuation:

Passing milestones, meeting deadlines, organising data engineering teams
  • Managing and training teams of data scientists Possibility of internship – thesis supervision
  • Working closely with the Data/Big Data teams
  • Study available data and define requirements in accordance with client demands
  • Recover and analyse relevant data related to business issues
  • Build algorithms to improve search and targeting results
  • Develop predictive models to anticipate the changes in data and trends relating to the company’s activity:
    • Model data analysis results to make them readable and usable by operational staff (functional, statistical and metric reports, data visualisation, etc.)
    • Business recommendations to senior management to improve processes/decision making
  • Definition of data storage and management solutions, in collaboration with the IT Department and Data Engineers
  • Technology monitoring and a source of ideas regarding new technologies
  • Ability to intervene technically and validate the good practices of data scientists
  • Ability to work in a variety of environments and work with people of different backgrounds
You will take part in the recruitment process for future employees

Profile

PhD or Statistical Engineer specialised in data science, with several years of experience

  • You have previous experience in managing and developing Data Science projects
  • Research and Development of Machine Learning algorithms
  • You are an educator and enthusiastic, able to supervise teams of engineers and researchers in Data Science
You are passionate about Data and its environment, are able to analyse complex, new customer issues, manage projects independently, question existing systems, and a driving force with new ideas.

Areas of expertise and proficiency

In addition to expertise in data/feature engineering, you are comfortable with all forms of data management: text, image, video, structured, time series, etc.

  • Cloud: knowledge of the various players and highly proficient in cloud software (Google, AWS, etc.)
  • Big Data: Comfortable with Big Data technology: Hadoop, hdfs, map reduce, spark, kafka, hive, etc.
  • Databases: Knowledge about SQL and NoSQL databases and their implications
  • Git, Java, python/R, linux/shell scripts
  • Machine Learning: proficiency in the various ML algorithm libraries (classic algorithms, neural networks, deep learning)
You have in-depth knowledge of the different areas related to machine learning, semi/unsupervised algorithms, clustering, dimensionality reduction, online learning, reinforcement learning, etc.