Senior Manager, Data Science (Fraud Risk Analytics) at Zip Co

Analytics & Data Science, Permanent, Sydney sydney analytics
Description
Posted 1 months ago

About us 

We are Zip, a rapidly expanding global fintech headquartered out of Sydney, Australia with a growing presence focused in the US and UK markets.

 We're here to simplify how the world pays for what they need by connecting merchants with consumers and offering them fair and seamless payment solutions, everywhere. We’re also the brains behind Pocketbook, which helps almost a million Aussies take control of their money and improve their financial wellbeing.

 Our values are at the heart of everything we do. They form our Mamba mentality - how we’re better than yesterday, and are used to create game-changing experiences for our customers and our people. 

Central to our goal is our Analytics and Data Science function, who build the models that underpin our products, provide the insights that shape our plans, and run the experiments that move our business forward. 

About the role

As a Senior Manager in our Data and Risk team, you will own the development and enrichment of fraud detection algorithms and provide advanced analytics to enhance Zip’s overall fraud detection and investigation strategies. This will include supporting the Fraud Review Team to identify high risk patterns and anomalies to enhance decisioning across the customer lifecycle.

In this role you will analyse structured and unstructured data using machine learning techniques to continuously improve application, real-time transaction and anomaly detection models; conduct exploratory analysis to identify behavioural trends and anomalies, support the implementation of new workflows to optimise operational activity related to fraud prevention and detection.

You will also work closely with the Fraud Investigations Team to quickly respond to rapidly evolving threats by recommending and implementing rule-based analytical solutions. And finally, you will support the development of analytical findings through reports, dashboards and data visualisations to monitor fraud trends.

This is a unique and exciting opportunity for a hands-on Data Scientist who can leverage not only their data discovery and model development skills, but also drive the end-to-end implementation of machine learning algorithms in an operational environment, ingesting data and scoring algorithms in an open-source tech stack.


To help us level up, you’ll bring:

  • Tertiary qualifications in a quantitative discipline (E.g. Mathematics, Statistics, Computer Science, Actuarial Studies, Economics).
  • 10+ years commercial analytics experience from a retail banking/consumer finance/payments/e-commerce environment, with experience in fraud detection and prevention.
  • Hands-on experience in modelling and the application of statistical/machine learning/deep learning techniques (E.g. GLMs, XGBOOST, k-means clustering, neural networks, random forests, anomaly detection etc.).
  • Strong exposure to analytical scripting languages, in particular SQL, Python, and R.
  • Previous experience with and good understanding of graph databases (e.g. Neo4J).
  • Bonus points for:

  • Post-graduate qualification/s (Masters or PhD).
  • Exposure to Big Data platforms (E.g. AWS) and applications (E.g. Hadoop, Hive, Spark).
  • Experience working with data visualisation tools (e.g. Tableau).
  • We’re looking for someone who always finds new boundaries to cross - a future Zipster who will obsess over excellence and make constant improvements for our customers. We’ve removed the red tape here to get things done quickly, so if you see a problem, own the solution. You've gotta hustle at Zip!

    If you only meet some of the requirements for this role, that's okay. We value a diverse range of backgrounds and ideas and believe this is fundamental for our future success. So, if you have the curiosity to learn and the willingness to teach what you know, we'd love to hear from you.

    We pride ourselves on creating an inclusive workplace that provides equal opportunities to all persons regardless of their age, cultural background, sexual orientation, gender identity and expression, disability, veteran status, or anything else.

    Benefits @ Zip

    -  Flexible working culture
    -  Share incentive programs
    -  Generous paid parental leave
    -  Birthday and wellness leave
    -  Epic offices with a casual dress code
    -  Fun team with high-growth hustle
    -  Free breakfast and weekly lunches
    -  Heaps of social events

    Join us on our mission to be the first payment choice, everywhere and every day.