Data Analytics Manager, Lending Indonesia

Life at Grab:

At Grab, every Grabber is guided by The Grab Way, which spells out our mission, how we believe we can achieve it, and our operating principles - the 4Hs: Heart, Hunger, Honour and Humility. These principles guide and help us make decisions as we work to create economic empowerment for the people of Southeast Asia.

Get to know the Role:

• As Data Analytics Manager for Indonesia, Lending business, you will be the centre point of contact for matters relating to data, dashboards, regulatory reporting, partnership portfolios, matters of data protection, alternative data, merchant lending and other day to day data support to the teams working closely with commercial and credit risk teams.
• Candidate should be hands on with analytics, data management, statistical and econometric modelling and SQL ETL tasks.
• Over time and with growth in size and scale of Indonesia business, the candidate will be supported by direct reporting team members, but for now this person will be a senior individual contributor.
• You will coordinate closely with the Singapore based regional Data organization and support regional initiatives on topics of data science and data analytics.
• Reporting to regional Head of Data Science & Analytics for Grab Financial, Lending business.

Key day to day tasks:

• Liaison with country credit bureau, regulators for the data reporting needs.
• Solve for country businesses’ finance reporting needs.
• Lead country level data audits to successful completion.
• Determine and acquire the datasets needed to be collected from internal and external sources and banking partners
• Design and implement databases and data schemas for new products and digital solutions
• Management of campaign reporting, MIS, analysis and derivation of key success KPIs
• Design and ownership of Dashboard in Tableau, Holistics, other ETL and MIS and dashboard reporting
• Work with regional data scientists, technology teams and other functions to deep dive on data solutions and prioritize business and information needs
• Assist data science teams in developing tools, metrics, and systems to analyze large-scale internal and external datasets to identify opportunities to improve solutions’ efficiency, accuracy for a more targeted product offering.
• ETL, Profiling and segmentation of datasets for tactical data mining tasks
• Test for incoming data quality (exploratory data analysis) and build and execute UAT test cases at the point of deployment of analytics models

The must haves:

• A Bachelor's/Master’s degree, preferably in Analytics, Statistics, Software, Mathematics, Economics, Computer Science or Engineering
• 8-12 years relevant work experience in BI, Analytics, Data Science roles (breadth of analytics experience a plus)
• Expert in SQL/Presto, Python coding skills
• Good in Tableau, PowerBI and building dashboards
• Proficient in Excel and PPT
• Strong analytical skills with the ability to collect, organize and analyse significant amount of information with attention to detail and accuracy
• Knowledge of data models, data mining and segmentation techniques
• Self-motivated and independent learner
• Detail-oriented and efficient time manager who thrives in a dynamic working environment
• Good in business communication
• Retail banking, FinTech, Credit Bureau experience preferred.

We recognize that with these individual attributes come different workplace challenges, and we will work with Grabbers to address them in our journey towards creating inclusion at Grab for all Grabbers.

About Grab

Grab is the leading superapp platform in Southeast Asia, providing everyday services that matter to consumers. Today, the Grab app has been downloaded onto millions of mobile devices, giving users access to over 9 million drivers, merchants, and agents. Grab offers a wide range of on-demand services in the region, including mobility, food, package and grocery delivery services, mobile payments, and financial services across 428 cities in eight countries

Join us today to drive Southeast Asia forward, together.