Data Scientist - Fraud

Zip Co Limited

Who is Zip? Join the Zipfam! 

Want to work for a fintech unicorn? Well now’s your opportunity! 
  
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. You'll be ingesting data and scoring algorithms in an open-source tech stack!

What are we looking for? 

The successful candidate will be responsible for the development and enrichment of fraud detection algorithms and provide advanced analytics to enhance our overall fraud detection and investigation strategies.

You'll be supporting the Fraud Review Team to identify high risk patterns and anomalies to enhance decisioning across the customer lifecycle.
  
More importantly, you’ll be passionate about numbers, machine learning and the application of analytics to solve real-world business problems in an organisation without red-tape or data silos!

What will your day look like?

  • Analysing structured and unstructured data using machine learning techniques to continuously improve application, real-time transaction and anomaly detection models
  • Conducting exploratory analysis to identify behavioural trends and anomalies
  • Supporting the implementation of new workflows to optimise operational activity related to fraud prevention and detection
  • Analysing and utilising graph databases to conduct social network link analysis that identifies suspected fraud and high-risk clusters
  • Working closely with the Fraud Review Team to quickly respond to rapidly evolving threats by recommending/implementing rule-based analytical solutions
  • Working with engineers to design machine learning solutions that operate effectively at scale
  • Supporting the development of analytical findings through reports, dashboards and data visualisations to monitor fraud trends

What you will need to succeed in this role:

  • Tertiary qualifications in a quantitative discipline (E.g. Mathematics, Statistics, Computer Science, Actuarial Studies, Economics)
  • 3+ years commercial analytics experience from a retail banking/consumer finance/payments/e-commerce environment, with a strong preference to experience in fraud detection and prevention
  • Hands-on experience in modelling and the application of statistical/machine leaning/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)
  • Strong communication and stakeholder management skills

It would be extra special if you have:

  • 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)

Why you will want to become a Zipster!

  • NOW is the best time to join - we are scaling and you will have the chance to really contribute and excel in your career.
  • We have state of the art offices in the CBD.
  • Our offices are fitted out with the latest technology and tools, designed with smart spaces to make work more fun!
  • Flexible working hours and working from home days.
  • Breakfast is yummy and waiting for you daily.
  • Loads of social events and Friday drinks.
  • Staff discounts for Zip products, movie tickets, retail stores and much more.
  • Chance to win $500 per month.
  • Friday massages.
  • Competitive share programme for ALL employees – we ALL share the rewards of working together and building great products.
  • Regular fundraisers and a a paid leave day every year to undertake voluntary work as Zipcares.
  • We promote diversity!

And there is so much more, APPLY now and we would love to tell you more about what it's like to become a Zipster at Zip! 
  
We will review all resumes and love to update all candidates about their applications. We appreciate the time it takes to apply for a role and know how it is important it is to stay in touch with top talent!
  
Recruitment agencies: We are not engaging with recruitment agencies for this role and do not accept unsolicited resumes.

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Date Posted
19 Aug 2019
18 Sep 2019
Location
Sydney NSW 2000
Category
Trades & Services

Skills
UNSTRUCTURED DATA
NEURAL NETWORKS
Hive
K-MEANS
LEARNING SOLUTIONS
MACHINE LEARNING
NEURAL
NEURAL NETWORK
QUANTITATIVE
DESIGN
RANDOM FOREST
RANDOM FORESTS
REAL-TIME
RECRUITMENT
RETAIL BANKING
STATISTICS
ECOMMERCE
DEEP LEARNING
TABLEAU
MANAGEMENT
CLUSTERING
ANOMALY DETECTION
AMAZON WEB SERVICES (AWS)
ALGORITHMS
ADVANCED ANALYTICS
ACTUARIAL
DATABASES
MICROSOFT EXCEL
SCRIPTING
HADOOP
PYTHON
SQL
Perks
Staff Discounts
Flexible Working Hours
Friday Drinks