Data Science & Analytics
- Work on data science and analytics challenges and use cases of Launchpad projects or PoCs
- Create or improve services, processes and offerings, by using state-of-the-art machine learning, advanced analytics and artificial intelligence techniques
- Support the Lead Data Scientist in end-to-end delivery of machine learning and data science projects including business communication and requirements gathering
- Take a hands-on approach towards innovation, developing new analytics models to leverage data that can demonstrate business value – data integration and exploration, visualization and interpretation of results
- Exhibit a try fast, fail fast attitude with a growth mindset that empowers experimentation.
- Good modelling background including but not limited to classification, clustering, recommendation systems, deep learning, reinforcement learning, natural language processing etc.
- Collaborate closely with data owners to ensure the technical execution is aligned with general technical guideline and guardrail.
SKILLS REQUIREMENTS OF THE POSITION
- Bachelors/Masters Degree/ PHd in fields related to Data Science/Mathematics/Applied Statistics/Machine Learning is preferred
- Minimum 1-3 years of experience (professional or academic) in Data Science and Analytics areas
- Fluent in French & English to Interact with French customers/ Stakeholders and provide data analysis in French-to-French speaking countries.
- Ability to work within a high degree of uncertainty and ambiguity or problem statements, able to break them down and define how to leverage data to achieve desired outcomes.
- Deep understanding on application design/development and engineering best practices
- Programming experience in some of Python, PySpark, SAS, SQL, etc.
- Candidates preferred with exposure to Data / Machine Learning / Artificial Intelligence / Blockchain, as well as exposure/passion in disruptive business models and new technologies
- Ability to deconstruct and optimize Deep Learning Architectures
- Hands-on experience creating production-ready/deployable models
- Experience working with platforms such as Linux, Docker and Kubernetes
- Experience working in startups, incubators, VCs or similar entrepreneurial roles, opensource contributions is a plus
