We are looking for a passionate, motivated, and innovative Principal Data Scientist, to join our innovation department.
What your day will look like:
Be part of the founding data-science team, implementing new and exciting features, end-to-end, along with the product team, focusing on the algorithmic and machine learning aspects embedded in all our products.
As part of the founding team, you will be able to grow as a data scientist and define the theoretical and technical directions, and you will enjoy a lot of autonomy, responsibility, and ownership.
Apply your scientific knowledge and creativity to analyze large volumes of diverse and unstructured data and develop algorithmic solutions and models to solve complex problems.
Characterize and break down product use-cases effectively, choosing the right formalization and tools to best tackle them.
Research, design and apply advanced data processing technologies and methodologies, from a research playground to production. Contribute best practices to our backend applications and help pick the right frameworks and tooling for next product.
Work closely with other team members, such as backend developers, product managers and data engineers, across all groups and departments.
Build and promote quick prototypes/POC/demos to conceptualize innovative ideas
Be responsible for the entire algorithmic lifecycle in the company: data analytics, prototyping of new ideas, implementing algorithms and machine-learning models in a production environment and then monitoring and maintaining them.
Turn algorithm prototypes into shippable products that will have a significant and immediate impact on the companys revenue.
Requirements: Proven strong expertise (8+ years) as a data scientist and machine-learning researcher.
Proven strong expertise (8+ years) in Python, with a production-level design and coding skills and hands-on experience with coding machine learning / statistical modeling based solutions
M.Sc. in Computer Science, Mathematics, Engineering or a related field, with strong theoretical background in supervised & unsupervised modeling and various other statistical modeling techniques
High-level experience with databases approaches, such as SQL and document-oriented (e.g. MongoDB) and big data
Experience in data analysis and visualization
Strong problem solving and critical thinking skills
Can-do approach
Background in Cybersecurity - an advantage
Theoretical and practical background in Generative AI - an advantage
This position is open to all candidates.