Lead Data Scientist

Who are we?

OneCredit is Malaysia's newest Credit Reporting Agency registered under the Ministry of Finance. We compile and maintain individual and business credit information to generate reports and scores to help businesses and consumers manage risk, make informed decisions, and achieve their financial goals. Beyond that, we are an information services and technology company specialising in big data analytics, delivering data-driven insights that support decision making in businesses and financial institutions.

Role Overview

We are hiring a Lead Data Scientist to lead one of our core AI systems and scale it.

You will be the tech lead for a project with multiple data scientists and ML engineers, scaling the system to handle a growing number of new use cases and much higher volume. The role is hands-on: you will still build, evaluate, and ship. As the team grows, so does the scope.

You will work directly with the Head of Data & AI.

Key Responsibilities

• Be the tech lead for a project with multiple DS and MLEs: set direction, review work, and keep delivery on track without becoming the bottleneck.

• Take on people management as the team grows: 1:1s, feedback, and developing the DS and MLEs you lead.

• Evaluate and scale experiments for a novel system, and take what works into production, then monitor and keep improving it.

• Scale it for volume: throughput, latency, cost, and reliability.

• Build repeatable tools and ways of working so each new use case ships faster than the last, instead of one-off projects.

• Set the bar for experimentation, evaluation, reliability, and monitoring, with an evaluation set and regression checks for every use case.

• Make human review scale without adding a validator for every new use case.

What it takes to succeed in this role

We are a small team shipping AI systems that banks rely on. You will do well here if you:

• Find the problems worth solving and own them end to end, without waiting to be told.

• Set direction on a novel idea and execute on it consistently.

• Make trade-off calls under uncertainty and say no to bad scope.

• Write well, and can present to non-technical people to get buy-in for your work.

• Think agent traces are the new oil.

• Dream about automating tedious human work with AI.

• Would rather ship a scrappy experiment this week than a perfect plan next quarter.

Requirements

• 5+ years in data science or ML (3+ if you are already at Senior level), with ML or LLM systems shipped to production that you were accountable for.

• Experience leading a small team of data scientists or ML engineers.

• Experience scaling a system from one use case to many, and to much higher volume.

• Strong ML foundations and hands-on depth with LLMs and document AI.

• You know how LLM evaluation works (eval sets, LLM-as-judge and its limits, regression testing) and can defend your results when they are challenged.

• Production-quality Python, and a working understanding of how models are deployed and monitored.

• Fintech, credit, or regulated-industry experience is a plus, not a must.

Our tech stack

• Languages and APIs: Python, FastAPI

• Orchestration and messaging: Temporal, Dagster, RabbitMQ

• Data and cloud: Snowflake, AWS

• CI/CD: GitHub Actions

• Observability: Datadog, Langfuse

You don't need all of it, but you should be comfortable picking it up.

What success looks like in your first 30 days

• In your first two weeks, you are shipping experiments on the system.

• By week three, you have a plan, agreed with the Head of Data & AI, for how the team drives the product forward.

• By the end of month one, the team is executing on that plan.

What We Offer

• Competitive basic salary

• Opportunity to grow with a high-growth credit intelligence company

• Be part of a company transforming the credit intelligence industry in Malaysia

• Fast career progression for high performers

Why Join Us?

• Lead a production AI system on real, high-stakes financial data.

• Room to experiment, and a team that ships what works.

• Early team with leadership opportunities.

Interview process

1. HR screen

2. Main interview with the Head of Data & AI (1–2 hours): a deep dive on a system you have shipped, a live case study on scaling one of ours, and how you lead and own work

3. CEO