Requirements

• Native in Indonesian language and proficient in English

• Based in Jakarta and willing to work face to face in client's site

• Have at least 5-7 years of working experience in business intelligence and/or descriptive, predictive, or prescriptive analytics

• Ability to analyze large datasets and synthesize key findings to provide recommendations via descriptive analytics and business intelligence

• Have the knowledge on metrics, measurements, and benchmarking

• Data and analytics experience such as working with data analytics software (e.g., Python, R, SQL, SAS) and building, managing, and maintaining database structures

• Advanced Word, Excel, and PowerPoint skills

• Have experience in banking industry (preferably consumer banking)

• Can work independently and drive progress with banking clients

• Experience managing clients or internal stakeholders and ability to perform multiple tasks with multiple clients in a fast-paced, deadline-driven environment

• Have hands-on experience in consumer banking debit or credit card portfolio optimization analytics, including relevant analytics approaches and modelling

• Demonstrate basic SQL writing ability through an on-the-spot query-writing exercise; candidates should be able to construct logic independently rather than rely on copied queries

• Understand the objective of each modelling approach, why one approach is selected over another, and how to validate that model outputs are accurate and appropriate

• Be coachable and able to understand guidance and case objectives, respond to the question asked, and adjust their approach after feedback

Roles and Responsibilities

• Conduct analysis using Mastercard’s and or client’s data

• Create segmentation, benchmarking, rule based-modelling, and performance tracking

• Review analytics deliverables to ensure accuracy, quality and timeliness

• Support developing project deliverables

• Support implementation of the agreed plan and mitigation actions agreed in the weekly cadence and steering committee meetings

• Support alignment between all stakeholders and help to coordinate as well as prepare the materials for biweekly progress updates and steering committee

• Create portfolio segmentation using factors such as merchant category code (MCC), dormancy and recency, and customer personas (e.g., traveller or foodie)

• Develop predictive models, such as propensity to travel and propensity to attrite

• Track campaign performance and assess results against objectives

• Generate data insights for regular portfolio performance reviews

• Assess candidates’ basic SQL skills through a live query-writing exercise

• Assess whether candidates can explain model objectives, approach selection, and validation of model accuracy and outputs