These are associate level roles and not affiliated with the CBA Graduate Program. These applications are open to all visa types.
Analytics & Information (A&I) is the machine learning and data science group at CBA that brings together datasets from all across the Bank to enable advanced analytics and business intelligence.
We are looking for Associates to join A&I’s data science team. Data science is a technical career that is increasingly in demand. It allows you to bring your technical abilities to the task of solving real world business problems using the most cutting edge technologies and techniques from computer science and statistics. At A & I as a data scientist you build solutions that will have material impact on our customers lives; we are the biggest bank in Australia, and one of the biggest in the world, and we provide a unique capability to understand the financial behavior of up to 40% of Australia’s population. We work alongside many businesses and people across the bank including engineers and software developers, actuaries, economists, finance and business experts. All whom look to our team to help them solve a variety of different problems, from helping them collate and visualize data, design interactive dashboards, identify statistical patterns and create predictive models.
As an Associate Data Scientist you must be bright, curious and passionate about turning data into actionable insights. Day to day you will find yourself analysing data, building models, designing experiments, and trying to figure out how to deal with large and complex datasets- we handle petabytes of data. The environment you will work in is highly collaborative- working on the Hadoop ecosystem, you will have the opportunity to work closely with data engineers to create scalable, end-to- end solutions for our customers. You will also be expected to work closely with the business to understand the problem and deliver optimal and efficient solutions through effective written and verbal communication and presentations. The problems you will work on will also be diverse, covering anything that could impact business, our customers or the community; with previous work having been in customer propensity models, process optimization, financial crimes and recently, dynamic population modelling.
You will be joining a large and experienced Data Science team that offers many opportunities for mentoring and learning. The team come from diverse backgrounds (including computer science, electrical and mechanical engineering, mathematics, statistics, biomedical science and physics), all of whom are passionate about data and are committed to innovation through technology, idea generation and independent thought. You will also be expected to actively contribute back to the scientific community through input to open source projects and scientific literature, review of existing literatures and new methods and/or participation in academic collaborations.
Please apply if you are:
- Practiced at working with data and extracting meaningful insights from it
- Comfortable with using quantitative and statistical techniques (e.g. machine learning, forecasting, and predictive modeling) to solve problems
- A creative and innovative problem solver who wants to turn data into insights,
- A superior communicator, with the ability to explain content to multidisciplinary audiences (both technical and non-technical)
- Driven, curious and eager to tackle a wide variety of problems, and are able to learn and work independently
- Masters and/or PhD degree in Quantitative Field (Computer Science, Statistics, Mathematics, Engineering, Economics or related fired)
- Solid grounding in applied mathematics and statistics, including expertise in applying these techniques to structured and unstructured data.
- Demonstrable skills in problem solving, scoping analytic problems, and selecting analytic modeling frameworks
- Excellent verbal, written, organizational and visual communication skills
- Demonstrable skills in data visualization (E.g. MATLAB, R, matplotlib, gnuplot)
- Experience using R, MATLAB, Python or other scripting languages for data prep, analysis, and/or machine learning
- Research experience in a quantitative field (preferably statistical research)
- Independent education through open online coursework and capstone projects
- Experience with machine learning algorithms (Generalised Linear Models, Boosting, decision Tree, NN, SVM, Ensemble)
- Proficient in programming languages in R, Python and/or Scala
- Contribution to any of: data-science forums, Kaggle, Hack-A- thons, scientific papers or communication; and/or involvement in open-source projects will be highly regarded
- Business facing experience
- Experience with SQL or querying from relational databases
- Experience Working with large datasets