As a Data Scientist in our London office, you will leverage your expertise for our platform in the fast-paced world of online gaming and sports betting. Through innovative data analysis and cutting-edge tools, you’ll play a key role in using data insights to enhance our services for hundreds of thousands of daily users.

What you’ll be doing:

• Design and implement scalable data pipelines to support machine learning workflows.
• Develop and enhance machine learning solutions to scale with business needs.
• Support a research team by processing and analyzing large volumes of data.
• Provide technical support in product integration to ensure seamless functionality.
• Build and maintain cutting-edge personalization models and recommendation engines that leverage user behavior, historical data, and real-time interactions to boost customer engagement and satisfaction.
• Clean, preprocess, and transform large datasets to create features optimized for machine learning; implement data pipelines to streamline model training and inference.
• Stay up-to-date with the latest machine learning techniques, researching and testing new algorithms to enhance recommendation system accuracy and effectiveness.
• Collaborate with data scientists, software engineers, and product managers to understand business needs and translate them into impactful machine learning solutions.
• Optimize and scale machine learning models for high-throughput, real-time recommendation systems, ensuring they are robust, efficient, and ready for production.
• Implement monitoring systems to track model performance, troubleshoot production issues, and proactively address data-related challenges.
• Document machine learning models, algorithms, and workflows for knowledge sharing and adherence to best practices.

We're looking for someone with:

• A Bachelor’s degree in Computer Science, Technology, or a related field.
• At least 5 years of experience in a data science or machine learning role.
• Proficiency with tools and technologies such as:
• Snowflake, AWS SageMaker, Databricks, Airflow, GitHub, Python, Kafka, Lambda, SQL, and Docker.
• Machine learning technologies like Scikit-learn or similar.
• Strong analytical and problem-solving skills with the ability to interpret complex data and develop actionable insights.
• Experience with real-time data processing and building data pipelines for large-scale production environments.
• A collaborative mindset, with proven success in cross-functional teams, effectively bridging business and technical requirements.

Bonus points for:

• Experience with Apache Spark.
• Experience with Hadoop.
• Experience with TensorFlow or PyTorch.