Data Scientist Specialist

Get To Know Our GX Bank Team

GX Bank Berhad - the Grab-led Digital Bank - is the FIRST digital bank in Malaysia, approved by BNM to commence operations. We aim to leverage technology and innovation to serve the financial needs of the unserved and underserved individuals, and micro and small medium enterprises.

We are driven by our shared purpose and passion to bring positive transformation to the banking industry, starting with solutions that address the financial struggles of Malaysians and businesses.

Get To Know The Role

• Develop and deploy Data Science and Analytical solutions for Regional Business Banking functions. Your impact will span across customer acquisition, retention, engagements, product development, pricing decisions, and addressing numerous business needs within Digibank.
• Manage and own the entire end-to-end lifecycle of building and validating predictive models along with their deployment and maintenance.
• Work alongside business, marketing, and other teams across the bank to craft solutions and drive product changes that are informed by your findings and aligned with business realities.
• Work independently or in a team to solve complex problem statements.
• The day-to-day activities: Build predictive models using a mix of machine learning methods and conduct data explorations to generate data-driven insights.
• Validate data-driven solutions by conducting experimentation with Product, Business and Marketing teams.
• Engineer predictive features from internal data assets to build refined customer profiles. Identify external data assets to bring into the model mix.
• Track model performance KPIs and improve performance of analytic models developed
• Stay current on cutting edge machine learning tools and approaches.
  
  

Must-Haves

• A self-starter who has a strong record of professional achievement, characterized by critical thinking, self-motivation, teamwork, and continuous learning.
• Minimum 3 years of experience in developing and deploying machine learning and predictive modeling solutions using extensive datasets, with a proven track record of achieving significant outcomes.
• Advanced degree preferred: Masters degree in Computer Science, Applied Mathematics, Statistics, Machine Learning, Data Science, AI or a related quantitative field.
• Capability to independently analyze data, generating insights and sound recommendations for stakeholders and management
• Extensive hands-on experience in coding and modelling skills in SQL, Python, Spark, R, Presto, Hive proficiency.
• Experience in Cloud technologies is a must, AWS is preferred
• Experience with designing, running and analysing A/B tests and product experiments with a good understanding of hypothesis testing and the basic principles of Design of Experiment.
• Deep technical and data science expertise, including experience in Analytical methods: statistical modeling (e.g., logistic regression, time series, CHAID, PCA), supervised machine learning (e.g., random forests, neural networks), unsupervised learning, design of experiments, segmentation/clustering, text mining, network analysis and graphical modelling, optimization, simulation.
• Proven experience in building in-production models, including scripting, error handling, and thorough documentation
• Understanding of trade-offs between model performance and business needs.