Business Intelligence Lead

7 days ago


Jakarta, Indonesia Grab Full time

**Job Description**:
**Who We Are**

OVO is Indonesia’s first fintech unicorn and a leading digital payment and financial services platform serving Indonesians nationwide. Our mission is to open up access to financial services through products and services that are easy-to-use, secure and affordable. As part of the ecosystem of Grab, Southeast Asia's largest mobile-technology company, we're excited to bring even more innovations to better serve the financial needs of Indonesians.

Looking to be a part of the effort to drive financial literacy and financial inclusion across Indonesia? Want to collaborate with teams that work hard while still keeping a fun camaraderie, and are quick to support each other? Want to work where your contributions and ideas are not only welcomed, but strongly encouraged, no matter if you're an intern, staff, or manager? Come join us

OVO is currently open for The Business Lending Associate

**You Will**
- Integrate department, segment, and organizational strategy into the BI development process; clarity operating objectives, including their linkages to related BI areas.
- Make independent decisions regarding own work methods, occasionally in ambiguous situations with mínimal direction

**What You Need**
- Bachelor's degree in a quantitative field (Statistics, Business Analytics, Mathematics, Operations Research, Engineering, Informatics, Data Science).
- 5+ years of relevant experience and has experience in leading teams of Data Analytics or other leading edge analytics focus.
- Possesses a solid understanding of how organizational capabilities interrelate across departments and the ability to lead across large and matrixed environments.
- Experience in developing, maintaining and collecting structured and unstructured data sets for analysis and reporting.
- Experience creating advanced analytics to support business strategy.
- Experience identifying and resolving complex technical and operations problems.
- Experience building BI environments with significant scale and scope (Power BI, Tableau, SQL, BigQuery, Airflow, etc.).
- Experience with incorporating descriptive analytics and predictive modeling techniques into BI tools



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