Data Scientist - AI (Collection)
At a glance
Mid-level AI Research role at Kredivo Group. Jakarta · full-time.
Pay not stated AI Research salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build LLM-based collection chat and voice assistants, including WhatsApp and in-app experiences
- Use speech-to-text and LLMs to review collection calls and chats against SOPs, then share operational insights
- Improve models that guide whom to contact, when to reach them and which channel to use
- Run experiments on collection KPIs and work with engineering and operations to launch and refine models
What you bring
- At least two years in data science or machine learning, ideally in lending, fintech or a related listed area
- A bachelor's or master's in a quantitative discipline such as computer science, statistics or mathematics
- Strong Python and SQL skills, plus practical work with LLMs and machine-learning libraries
- Fluent Bahasa Indonesia, solid English and the ability to explain technical work to nontechnical partners
Who this fits
This mid-level role suits a hands-on data scientist who enjoys building, testing and improving models in production. You'll work with Collection Ops, Product and Engineering from the Jakarta office.
From the employer
Kredivo is hiring a Data Scientist – AI (Collection) in our Jakarta office to build AI-powered products that change how we collect payments from customers. This position will report to the Lead Data Scientist – Collection & SPG and will be accountable for designing, shipping and measuring AI solutions across the collection journey, from early reminders to late-stage recovery.
In this role you will also be responsible for driving AI transformation within Collection: building conversational AI (chatbots and voice bots/robocalls), automating desk collection audit processes, and applying LLMs to collection workflows. In addition, you will be responsible for proving business impact through rigorous experiments and working closely with Collection Ops, Product and Engineering to put models into production.
About the job:
- To design and build LLM-powered collection assistants (WhatsApp/in-app chatbots, AI voice agents/robocalls)
- To build automated audit and analysis of desk collection calls and chats, using speech-to-text and LLMs to check them against collection SOPs at scale and turn them into insights for Collection Ops
- To develop and improve predictive models (e.g. propensity-to-pay, contactability, best channel/time to contact) that decide who to contact, when and how
- To design and analyze A/B tests that measure impact on collection KPIs (roll rate, recovery rate, cost per collection)
- To work with Engineering and Ops to deploy, scale and iterate on solutions, and to make sure they follow our internal collection guidelines
About you:
- Bachelor's or Master's in Computer Science, Statistics, Mathematics, Engineering or a related quantitative field
- 2+ years of experience in data science or ML, ideally in fintech, lending, collections or customer operations
- Strong Python and SQL; hands-on with ML libraries (scikit-learn, XGBoost/LightGBM, PyTorch or similar)
- Hands-on experience building with LLMs: prompt engineering, RAG, function calling/agents, and LLM APIs or open-source models
- Exposure to conversational AI or voice tech (chatbot frameworks, STT/TTS, voice bot platforms) is a strong plus
- Solid grounding in experimentation and statistics (A/B testing, causal inference basics)
- Experience deploying models to production or working with MLOps tools (Airflow, Docker, cloud platforms) is a plus
- Fluent in Bahasa Indonesia and good English; able to explain technical work to non-technical stakeholders
- Product-minded and hands-on: you like shipping, measuring and iterating quickly
If this sounds like you, we would love to hear from you!