At yzr we are building our Web Platform using a hybrid of Code and No-Code technologies. [Bubble.io](http://Bubble.io) is our main tool for building the front, and Apis and Airflow in Python for building the back. These choices have had great positive impacts on the team because, we can build and iterate faster. We do not have to deal with hosting of our application, and front development has become much more accessible to people. But these choices also have drawbacks, we do not have complete flexibility on how to build our features. Bubble itself is a relatively new tool which is also evolving, so we sometimes have to fight the bubble functionalities to get the desired results. Finally making data operations faster is a big challenge.
Our SAAS solution is based on AI Deep learning algorithms. Those algorithms are mainly NLP/NLU/Word Embedding/Tagging algorithms.
We are looking for a Lead Data Scientist to join our team and help us improve and achieve our objectives of 2022.
- Create new AI Algorithm and Improve our general current algorithms
- Speed UP and improve the quality of our R&D
- Improve response times of our AI Algorithms
We are looking for a Python lover / fanatic to join our team and help us improve and achieve our objectives of 2022.
Requirements
- Doctorate or bachelor’s degree in Data Science.
- 3-5 years work experience designing, executing, and supporting Deep Learning (NLP,NLU,Word Embedding,Tagging,…) algorithms.
- AWS, AZURE, GOOGLE or OVH Certified Solutions Architect certification will be appreciate.
- Good knowledge in python scripting languages and experience with relational databases are also helpful.
- Extensive experience with at least Docker/Kubernetes system.
- Exceptional knowledge and understanding of data modelling best practices.
- Interpersonal skills: The job of a lead Data Scientist will require to drive a team of at least 2 data scientists. So it is vital that the lead can understand the needs, translate them to the team, propose solutions, manage priorities and report to the CTO and other tech leaders.
- Communication skills: It is important that lead Data Scientist possess good written and verbal communication skills to effectively articulate complex AI reports and relate with backend team that will integrate algorithms in the AI.
- Practical knowledge of Agile Software development methodology.
- Ops skills (exceptional knowledge of CI/CD and automate testing).
- Leadership skills
Responsibilities
- Collaborate and makes proposals for our AI team on their engineering work, and helps the team members make informed decisions in alignment with the tech department strategic plans.
- Expose technology and organizational needs throughout the tech department.
- Teach, mentor, grow, and provide data science advices, individual contributors in our AI team.
- Play a central role in technical, business, and organizational contributions affecting the AI team.
- Plan improvements and features with a 6 month view.
- Solve AI problems of the highest scope, complexity, and ambiguity for the tech department.
- Interface with EMs and Senior management, and enables Staff Engineers to engage on department-level aspects of larger (tech department wide) initiatives.
- Look for innovation opportunities in our AI team with a willingness to experiment and to boldly confront problems of large complexity and scope.
- Propose initial technical implementation which supports architectural changes that solve scaling and performance problems.
- Ensure that OKR level goals are aligned with our AI team.
- Guide conversations to remove blockers and encourage collaboration in the AI team.
- Provide a point of escalation for tech department teams facing complex technical AI challenges.
- Attain a measurable impact on the work of tech department teams regarding AI.
- Interact with product department and other external stakeholders as a consultant and spokesperson for the work of the tech department regarding AI.
- Expose the AI work of the tech department and their business impact internally.
- Knowledgeable in all specialities practiced within the tech Department
- Implementation and the maintenance of CI/CD and automate testing
- Writing of technical AI documentation
Recruitment process:
- Technical test
- First interview with our PHD Data Scientist
- Second interview with our CTO