Senior Associate Data Scientist

Roles & Responsibilities:

1. Analyse complex data sets to extract insights and identify trends.
2. Develop predictive models and algorithms to solve business problems.
3. Work on deployment of models in production.
4. Collaborate with cross-functional teams to understand requirements and deliver data-driven solutions.
5. Clean, preprocess, and manipulate data for analysis through programming.
6. Communicate findings and recommendations to stakeholders through reports and presentations.
7. Stay updated with industry trends and best practices in data science.
8. Contribute to the development and improvement of data infrastructure and processes.
9. Design experiments and statistical analysis to validate hypotheses and improve models.
10. Continuously learn and enhance skills in data science techniques and tools.
11. Strongly support the adoption of data science across the organization.
12. Storytelling – Good Communication and storytelling skill and experience to present to senior stakeholders and business.
13. Strategic Thinking – Commercial acumen, comfortable in fast moving environment and an aptitude to question and challenge stakeholders & fellow team members to get to the best outcomes
14. Risk Mindset – All CommBank employees are expected to proactively identify and understand, openly discuss and act on current and future risks.
15. Research and Development: Drive internal research initiatives and contribute to the AI community

Essential Skills:

1. Strong hands-on programming experience in Python (mandatory), SQL, Hive and Spark.
2. More than 6 years of relevant experience.
3. Ability to write well designed, modular and optimized code.
4. Knowledge of H2O.ai, GitHub, Big Data and ML Engineering.
5. Knowledge of commonly used data structures and algorithms.
6. Solid foundation of Statistics and core ML algorithms at a mathematical (under the hood) level.
7. Good to have: Knowledge of Time Series, NLP and Deep Learning and Generative AI is preferred.
8. Good to have: Knowledge and hands-on experience in developing solutions with Large Language Models.
9. Must have been part of projects building and deploying predictive models in production (financial services domain preferred) involving large and complex data sets.
10. Good to have: Knowledge and hands-on data engineering or model deployment
11. Strong problem solving and critical thinking skills.
12. Curious, fast learning capability and team player attitude is a must.
13. Ability to communicate clearly and effectively.
14. Demonstrated expertise through blogposts, research, participation in competitions, speaking opportunities, patents and paper publications.
15. Most importantly - ability to identify and translate theories into real applications to solve practical problems.

Education Qualifications:

: Bachelor’s degree in Engineering in Computer Science/Information Technology.