Develop and deploy big data anti-fraud detection solutions and models using Python and PySpark, with potential to improve them with machine learning algorithms
Job Summary
Develop and deploy big data anti-fraud detection solutions and models using Python and PySpark, with potential to improve them with machine learning algorithms.
Collaborate closely with product owners, analysts, developers, and testers to ensure the software built is reliable and easy to maintain in production.
The company offers a continuous learning culture with coaching and support, flexible Work from Home options, and a comprehensive benefits package including private healthcare and life insurance.
Matching Summary
Develop and deploy big data anti-fraud detection solutions and models using Python and PySpark, with potential to improve them with machine learning algorithms.
Skills & Requirements
Must-have
Python and PySpark for large data volumes
Pandas, NumPy, Scikit-learn, TensorFlow
SQL, Oracle, Hive, Impala databases
Distributed computing principles
Unix/Linux environments
Spark, HDFS, Hive, YARN, Kerberos
Version control systems like Git
Nice-to-have
Machine learning algorithms and models
Hadoop ecosystem experience
Performance optimization
DevOps practices like CI/CD
Shell Scripting
Problem-solving skills
Team collaboration and communication
Key Requirements
Bachelor’s degree in Computer Science or IT-related discipline (or equivalent experience)
Proven experience developing with the described tools stack