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Hybrid Data Scientist Data Scientist

Happening · United Kingdom · Hybrid

About the job

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 you 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