Data Scientist
Croatia · United Kingdom
Happening
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
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
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
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