Data Scientist

Croatia · United Kingdom

Apply now Apply later

 

As a Data Scientist in our Fraud Prevention team, you will leverage your expertise to build robust fraud detection models that safeguard 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 ensuring platform security and enhancing our services for hundreds of thousands of daily users.

What you’ll you be doing:

  • Fraud Detection Modeling
    • developing and optimizing traditional ML algorithms such as gradient boosted trees in fraud detection or anomaly detection domains
    • creating graph analyses and graph connection modelling
    • creating usable datasets for explorative analysis and turn clues into leads and insights for ML modelling
  • Data Engineering
    • using SQL, Spark or Python for explorative analysis and feature engineering in a heavy tabular data environment
    • building new and supporting existing microservices that enable product features
    • data engineering and working with relational DBs including data cleaning and preprocessing for ML pipelines and productionalization of the data pipelines using Snowflake, Airflow or DBT or similar tools
    • designing and implementing efficient ML pipelines
  • Collaborative Innovation
    • creating impactful ML solutions and owing their implementation and improvements
    • autonomously breaking down and estimating data science projects into timed deliverables
    • working closely with cross-functional product and engineering teams
    • communicating complex findings to stakeholders in a clear, understandable manner
  • Performance Tuning
    • optimizing models, continuously measuring and reacting to improve performance of ML solutions in production

We're looking for someone with:

  • A Master’s degree (or equivalent) in Data Science, Statistics, Mathematics, or a related field
  • Minimum 3 years of real world experience
  • Strong analytical background with proven expertise in exploratory data analysis, feature engineering, and working with tabular datasets
  • Proficiency in Python (including libraries like Scikit-learn) and SQL, with solid experience in relational databases
  • Good knowledge and experience of the broader data science domains, especially large language models or computer vision models used for anomaly detection
  • A track record in deploying machine learning pipelines using tools such as Airflow, SageMaker Pipelines or similar
  • A talent for clean coding, simple solutions, automated testing and continuous deployment
  • A passion for working in the cloud and automation
  • Excellent problem-solving skills and the ability to break down complex data science projects into achievable deliverables
  • Investigative mindset and attentive eye that looks for clues in tabular, sequential datasets

Bonus points for:

  • Experience with ML development and deployment tools such as ZenML, MLFlow, Airflow, …
  • Experience with AWS Services such as EC2, EKS, Cloudformation, Cognito, …
  • Experience with Kafka

 

Apply now Apply later

* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Job stats:  2  1  0
Category: Data Science Jobs

Tags: Airflow AWS CloudFormation Computer Vision Data analysis Data pipelines dbt EC2 EDA Engineering Feature engineering Kafka LLMs Machine Learning Mathematics Microservices MLFlow Pipelines Python RDBMS SageMaker Scikit-learn Security Snowflake Spark SQL Statistics Testing

Perks/benefits: Career development

Region: Europe
Countries: Croatia United Kingdom

More jobs like this