Lead, Data Science & Analytics

Overview

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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

Lead, create and execute the data science & analytics approach and roadmap in a startup atmosphere to support business goals with prioritization and delivery of actionable insights for business planning and execution. Lead and coach junior team members in developing and deploying analytical solutions and models across the Digibank's regional footprint to support functions including customer acquisition, customer retention, product development, pricing decisions, credit risk, fraud identification, and other business needs for retail and wholesale banking customers.

Responsibilities

• Create and execute the data science & analytics approach and roadmap in a startup atmosphere to deliver actionable insights for business planning and execution.
• Lead, coach and guide junior team members in developing and deploying analytical solutions, data science models, and analytics insights across the Digibank's regional footprint to support management and business teams across a variety of functions including customer acquisition, customer retention, product development, pricing decisions, credit risk, fraud identification, and other business needs for both retail and wholesale banking customers.
• Uncover and deliver actionable insights, trends and product recommendations to support the business, through dashboards and advanced visualization techniques.
• Conduct both historical and predictive analyses and convert into digestible, readable, and publicly-available insights.
• Design and develop Generative AI solutions to boost productivity and operational efficiency.
• Develop Generative AI / AI solutions to help the data team and other disciplines be more effective in debugging, data summarization and analysis of results.
• Manage and own the end-to-end MLOps life cycle including data exploration, training data, feature engineering, model development, validation, scoring, codes standardization, unit testing, deployment via API and model maintenance.
• Interface with business, risk & operation teams across the countries within the region to formulate solutions & product changes informed by findings and business inputs.
• Be the analytics technical expert with hands-on experiences who uses large data sets, creative and strong in applying varieties of machine learning methodologies / algorithms with different data tools in developing the models, running simulations & optimization.
• Be an analytics consultant for the business stakeholders to recommend and deliver both innovative and effective analytics solutions in driving continuous improvements and addressing business questions.
• Engineer predictive features from internal data assets to build refined customer profiles.
• Identify external data assets to bring into the model mix.
• Ensure high quality models and seamless integration, including model accuracy, automated quality checks, API latencies, deployment time etc.
• Write SQL scripts for data transformation.
• Ensure data accuracy and good segmentation of data sets for tactical data mining.
• Take on the responsibilities as a Technical Project Manager to drive projects, by partnering closely with the broader business, product, engineering and marketing teams to define requirements, design and analyze experiments that drive key product designs and marketing decisions.
• Creating data products which can be readily used by partners and business units across the bank.
• Act as the liaison officer between business units across the countries within the region and Data Engineering team on curating the data to be stored in a database and then used for dashboarding or analytics use cases.
• Thrive on sharing knowledge with others and helping collaborators grow to foster a positive and productive work environment.
• Stay current on cutting edge machine learning tools and approaches.

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