Data Scientist Lead
Location: Paris, France
Hybrid: on-site and remote from other places in France, EU, and UK.
We are looking for a Data Scientist Lead. At Motion!, we combine our strengths—ecosystem stakeholders network, modern technology, advanced analytics, data visualization, and industry specialist’s insights—with the expertise of our, corporate, venture capitalists and start-up partners. The results are, players in these ecosystems can tap into a worldwide circulation of ideas, knowledge, diligently vetted-innovation, talent, and capital. A powerful platform for the global start-up ecosystem network, uniquely prepared to provide smart solutions and services to our partners and customers.
What You'll Do
- Collaborate with our Vertical Lead’s to develop a Data Science roadmap
- Manage projects consisting of cross functional teams including Data Scientist, Software Engineering and Solutions Engineering
- Work on building out Motion’s suite of cutting-edge data science tools
- Collaborate with the Data Science team members to identify common problems and areas for automation and standardization
- Apply cutting-edge machine learning techniques at large scale to streaming data
- Conduct research into advancements in algorithms, computing and statistics and apply those insights to Motion !
- Communicate results to clients and end users. Incorporate their feedback into future Data Science projects
- Depending on candidate's experience level and demonstrated level of proficiency, may manage team up of up to 20 data scientists, machine learning-algorithms experts, data analysts, data modelling.
- PhD (preferred) or MS in computer science, statistics, physics or mathematics
- A minimum of 3 years experience working on data science/machine learning projects outside of academia
- Proven experience as a Data Scientist, Predictive Modeler, Analytics Professional or similar role
- In-depth understanding of various machine learning algorithms (e.g. SVM, neural networks), and techniques (e.g. cross-validation, feature selection, etc)
- Deep knowledge of open source statistical modeling tools such as R or Python
- Expert knowledge of at least one common data science framework, e.g., Python pandas/scikit-learn (preferred), TensorFlow or similar
- Strong communication skills
- Ability to define and execute a clear plan for data exploration, experiments, and conclusion
- Knowledge of Git or ability to learn it quickly
- Ability to frame problems and execute them independently is a must
- Industry experience in one of the following areas:
- Media & Publishing
- One or more published academic papers
- Previous contributions to patents are a plus
- Masters or Phd in a quantitative field, such as:
- Computer Science
- Industrial Engineering
- Operations Research
- Previous experience with Scala, Java, Spark, and/or MongoDB
Ideal job opportunity in Paris or remote work for professionals and expats seeking employment opportunities with English as the main working language.
The Data Scientist must be French native language speaker and/or fluent in English (able to lead and manage local and global teams and communicate in English with virtual teams from different locations).
This is a paid position commensurate with experience (a combination of equity, cash, and bonuses).
👀 Psst... we are giving you a trick: stand out when you apply by attaching to your resume a pitch, prez, link to a intro video, or other original content of your choice suggesting your ideas for the position or your past achievements. The goal is to discover you more!
Please apply via the job portal or send your CV / Resume along with a cover letter to talent (Code DSL).
** LOCAL CANDIDATES ONLY - NO VISA SPONSORING **
Motion ! is an early-stage technology start-up company based in Paris, France and New York City, U.S. Our vision is to build a smart innovation ecosystem that allows innovators, consumers, and businesses to do all aspects of business online. We at Motion are on a mission to make the world a more innovative and prosperous place, one community, one ecosystem at a time.