AVP, Credit Risk Data Scientist - (230001OH)

Key Skills

Analytical and Problem solving, Apache Hadoop, Apache Hive, Big Data Technology, Credit Risk, Data science techniques, Machine learning techniques, MLOps tools, Python Programming, PyTorch, Scikit-learn, SPARK Programming, SQL, Statistics, TensorFlow

Job Description

You will be given opportunity to take lead in researching, modelling and implementing Data Science solutions to drive risk management practices. By leveraging large structured and unstructured data and applying advanced analytics/machine learning techniques, you can mitigate potential risks and drive informed decision-making.

How you succeed

To succeed in this role, you need to have proficiency in machine learning, statistics and technical skillsets. Ability to work in a dynamic environment and willingness to embrace new technologies are pivotal for this role. Besides technical knowledge, having passion in data and enthusiasm in problem solving are equally important.

What you do

• Develop machine learning/deep learning models (non-regulatory model) to aid credit underwriting and decisioning.
• Build data pipeline to enable scalable solution.
• Deploy real-time and batch into Production credit management systems.
• Maintain Production models and continuously monitor/update model performance.
• Conduct routine and non-routine analysis with large, complex datasets and make recommendations.
• Support credit portfolio management with advanced analytics.
• Work with stakeholders to identify business needs and deploy analytical/machine learning solutions.

Who you work with

Group Risk Management works independently to protect, build, and drive our businesses. The team support good decision-making. With strong risk analysis. And a crucial, comprehensive role in sharpening our competitive edge. Optimising risk-adjusted returns. It’s about seeking and adopting best-in-class practices. Protecting the group from unforeseen losses. Keeping risk within appetite. Embracing change and managing growth in one of the world’s strongest banks.

Qualifications

Who you are

• You have a bachelor’s degree in Statistics, Mathematics, Computer Science or other quantitative fields.
• You have at least 4 years of working experience in building machine learning or statistical models.
• You are familiar with Python, common machine learning tools and frameworks (Scikit-Learn / Tensorflow / PyTorch) and SQL.
• You have experience with big data technologies such as Hadoop, Hive and Spark.
• You have knowledge in ML-Ops tools and Git.
• You possess strong analytical and problem-solving skills.
• You could multi-task and work independently.
• You are willing to take on new challenges and work in a fast-paced environment. 

Who we are

Singapore’s longest established bank, we’ve been helping people and businesses get what they want from life since 1932. How? By taking the time to truly understand people. From there, we provide support, services, solutions, and career paths that meet their individual needs and desires.

Today, we’re on a journey of transformation. Embracing technology and creativity to become a future-ready learning organisation. But for all that change, the entire focus of our organisation remains to be Simply Spot On. In everything we do.

And so whether you want innovate needs-based financial services. Work in friendly, supportive teams. Build lasting value in your community. Help people grow their assets, business, and investments. Take your learning as far as you can. Or simply enjoy a vibrant, future-ready career.

Your Opportunity Starts Here.

What we offer

Competitive base salary. A suite of holistic, flexible benefits to suit every lifestyle. Community initiatives. Industry-leading learning and professional development opportunities. Your wellbeing, growth and aspirations are every bit as cared for as the needs of our customers.