Kaizen Gaming
Data Science Team Lead
Job Description
We are Kaizen Gaming
Kaizen Gaming, the team powering Betano, is one of the biggest GameTech companies in the world, operating in 17 markets with 2 brands (Betano & Stoiximan).
We always aim to leverage cutting-edge technology, providing the best experience to our millions of customers who trust us for their entertainment.
We are a diverse team of more than 2.500 Kaizeners, from 40+ nationalities spreading across 3 continents. Our #oneteam is proud to be among the Best Workplaces in Europe and certified Great Place to Work across our offices. Here, there’ll be no average day for you. Ready to Press Play on Potential?
Let’s start with the role
As a team lead of the applied research team you will lead the efforts on implementing state of the art models to support AI products across the AI division. The ideal candidate will have extensive knowledge of SOTA architectures for tabular data and learning representations and hands-on experience on creating embeddings for production applications. This is a unique role for someone who wants to apply their research experience in the industry and lead a highly skillful team.
As an applied research team lead your main responsibilities will be:
- Build representations/embeddings for our customers and events that will be used on downstream applications;
- Train SOTA architectures for tabular data;
- Design custom architectures and pipelines to better encapsulate our customer and event data;
- Manage the applied research team members and guide their growth and career path development;
- Tech-lead and mentor fellow data scientists;
- Deliver models to support AI products across the AI division;
- Stay on top of the research and bring new promising developments.
What you’ll bring:
- 8+ years of experience in working with deep learning models;
- 5+ years of experience working with Python;
- Strong hands-on experience in data processing and model development, with proven track record in handling neural network training and working with core architectural components;
- Advanced knowledge of state-of-the-art deep learning architectures (including transformers) and demonstrated expertise in comparing/selecting optimal solutions for complex problems;
- Extensive experience in handling sophisticated data and modeling challenges, including temporal data processing, unsupervised and self-supervised learning approaches, with proven ability to troubleshoot complex model issues autonomously;
- Expert-level understanding of the complete ML project lifecycle, from problem scoping through deployment, with ability to handle ambiguous requirements independently;
- Previous experience in developing tabular data representations for production applications;
- Excellent communication and collaboration skills targeting a diverse audience from stakeholders to cross-functional technical teams;
- Experience in managing a team of data scientists;
We are looking for someone who is passionate about deep learning and representation learning and wants to connect research to the industry. Join us if you want to build models that will improve the experience for millions of our customers around the world.
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