Company Overview
AwanTunai is the leading vertical fintech player digitizing the offline FMCG supply chain in Indonesia. We solve for both operational and financing pain points through ERP software and integrated embedded financing for offline suppliers. Our traditional suppliers have aggregate annual sales of over $3bn+ and our embedded financing is on track to reach the annualized $1bn milestone next quarter. We have been growing revenues at an average 30% QoQ with 0.2% credit loss rates over the pandemic period across hundreds of traditional suppliers.
Our financial impact has won accolades from the UNCDF, Monetary Authority of Singapore, and with the IFC (World Bank Group) as a major shareholder. Management and our impact focused shareholders are committed to building a world class team regardless of diversity or location.
Our fraud management has won the trust of global banking groups (MUFG, OCBC), the largest local institutions (Bank BRI, Bank Mandiri), as well as global insurers (AA rated Munich Re) who protect our loan assets against credit default.
Role
AwanTunai is looking for a Data Scientist who will analyze and interpret complex data using statistical methods, machine learning, and domain expertise to extract insights, make predictions, and drive data-driven decisions.
Responsibilities
1. Conduct data exploration and discovery, and advanced data mining analysis on spatial-temporal data, user behavioral data, transaction data, machine/device log data, and others
2. Conduct experiments with data, build working prototypes to demonstrate ideas and results
3. Build scalable pipeline and data science models with open source systems or proprietary tools
4. Collaborate with business teams to contribute to new use cases for solving clients’ problems
5. Participate in IP creation, such as patenting, case studies, white papers and research papers as determined by business needs
Requirements
1. 3+ years experience of successful application of machine learning, data mining, and statistical analysis with demonstrable impact and proven track records
2. Demonstrated ability to take high level, loosely-defined business problems and identify precise, quantitative solutions
3. Working knowledge of databases and query engines for structured and unstructured data, data transformation (ETL), software development methodologies, and data science languages like Python, R, or others
4. Self-starter, capable of experimenting with various tools and developing own code and scripts for data manipulation, experimentation, algorithm implementation, accuracy measurements, etc.
5. Familiar with basic software development skills (agile methodologies, testing, version control, etc.)
6. Preferred to have advanced degree in Computer Science, Machine Learning, Operational Research, Mathematics or Statistics, or other equivalent subjects
7. Preferred to be familiar with basic software development skills (agile methodologies, testing, version control, etc.)