Happening Greater London, England, United Kingdom
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Happening Greater London, England, United Kingdom
Join to apply for the Staff Machine Learning Engineer role at Happening
As a Staff Machine Learning Engineer 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
o developing and optimizing traditional ML algorithms such as gradient boosted trees in fraud detection or anomaly detection domains
o creating graph analyses and graph connection modelling
o creating usable datasets for explorative analysis and turn clues into leads and insights for ML modelling
* Data Engineering
o using SQL, Spark or Python for explorative analysis and feature engineering in a heavy tabular data environment
o building new and supporting existing Erlang based microservices that enable product features
o 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
o designing and implementing efficient ML pipelines
* Collaborative Innovation
o creating impactful ML solutions and owing their implementation and improvements
o autonomously breaking down and estimating data science projects into timed deliverables
o working closely with cross-functional product and engineering teams
o communicating complex findings to stakeholders in a clear, understandable manner
* Performance Tuning
o optimizing models, continuously measuring and reacting to improve performance of ML solutions in production
Were looking for someone with:
* A Master’s degree (or equivalent) in Machine Learning, Data Science, Statistics, Mathematics, or a related field
* Minimum 4 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
Seniority level
* Seniority level
Mid-Senior level
Employment type
* Employment type
Full-time
Job function
* Job function
Engineering and Information Technology
* Industries
Technology, Information and Internet
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