Data Science Team Lead

Kaizen Gaming; Lisboa; Híbrido; EUR 70 000 - 90 000; Tempo integral

Resumo da oferta

A leading GameTech company in Lisbon seeks a Data Science Team Lead to guide a skilled team in delivering impactful AI products. The role requires deep expertise in machine learning and proven management experience. Ideal candidates have proficiency in Python, experience in deploying ML models, and strong analytical skills. Fluency in English is essential for success in this dynamic environment.

Qualificações

• Experience as a people manager.
• Expert knowledge of machine learning algorithms.
• Extensive hands-on experience in production ML models.
• Proficiency in Python’s ML ecosystem.
• Fluency in English.

Responsabilidades

• Lead and manage a team of data scientists and ML engineers.
• Translate product requirements into machine learning problems.
• Analyze data to derive insights.
• Run comparative experiments for model training.
• Mentor junior team members.

Conhecimentos

Leadership

Machine learning algorithms

MLOps

Python programming

Analytical thinking

Teamwork

Ferramentas

Spark/PySpark

Azure / Databricks

Descrição da oferta de emprego

We are Kaizen Gaming

Kaizen Gaming, the team powering Betano, is one of the biggest GameTech companies in the world, operating in 19 markets. 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 2.700 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 the team lead of an AI product team you will lead and guide the team\'s efforts in delivering high impact AI products. You will be at the core of AI developments, analyzing data, building machine learning models, collaborating with the tech team to create successful AI products.

The ideal candidate will combine a deep understanding of machine learning algorithms and proven extensive experience in building ML/AI powered applications in production along with previous experience of leading and managing AI teams.

As a Data Science Team Lead, you will:

• Manage a team of 5 to 7 skilled data scientists and machine learning engineers.
• Translate product requirements to machine learning problems and identifying areas where AI can have the most business impact;
• Analyze data to identify significant patterns and generate insights;
• Perform exploratory data analysis (EDA) and feature engineering to support the modeling process;
• Implement best practices on model selection, parameter tuning and optimization.
• Run comparative experiments for model training;
• Analyze ML metrics to evaluate different potential solutions;
• Manage the full lifecycle of AI features, from data collection to model design and to implementation and optimization in production environments;
• Mentor and share knowledge with more junior members and guide the team through complex projects.

What you’ll bring

Must-have:

• Previous experience as a people manager;
• Expert knowledge of machine learning algorithm and their theoretical foundations;
• Extensive hands-on experience in delivering machine learning models to production;
• Experience in developing MLOps solutions;
• Knowledge of Deep learning;
• Proficiency in Python’s machine learning ecosystem and solid software engineering skills (OOP);
• Strong skills in teamwork, communication, and analytical thinking;
• Fluency in English, both oral and written.

Nice-to-have:

• Experience with Big Data tools (Spark/PySpark) and cloud environment, ideally Azure / Databricks;
• Previous experience in pricing optimisation;
• Previous experience in forecasting;
• Previous experience in the betting industry.

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We are an equal opportunity employer committed to fostering a diverse and inclusive workplace. We welcome applications from individuals of all backgrounds, regardless of race, gender, religion, sexual orientation,or age.