Senior Data Scientist in Jakarta at Paystone

If you’re excited about building machine learning systems that don’t just generate insights—but actually power meaningful product experiences used by real customers every day—you’re going to like it here.

We’re looking for a Senior Data Scientist to join us at Paystone. In this role, you’ll help shape the future of how our products use data to drive smarter decisions, personalized experiences, and measurable business impact.

You’ll work closely with Product, Engineering, and BI to turn rich transactional and behavioural data into models and recommendations that land directly in the hands of merchants. From customer segmentation and churn prediction to lifetime value modelling and personalized recommendations, your work will influence the experiences customers interact with daily.

This isn’t a “build a model and throw it over the wall” kind of role. You’ll own the modelling lifecycle end-to-end—from framing ambiguous business problems and shaping datasets to evaluating performance and partnering with engineering teams on how outputs are delivered in production.

At Paystone, we’re growing quickly, investing heavily in AI-augmented development, and building systems that help businesses move faster and smarter. We’re looking for someone who loves solving meaningful problems, thrives in fast-moving environments, and is excited about the future of agentic workflows and AI-assisted engineering.

We’re a team of curious builders who care deeply about what we create and how we create it. There’s room to experiment, room to lead, and room to make a real impact. We collaborate often, challenge ideas openly, and genuinely enjoy building alongside people who are passionate about solving hard problems well.

In this role, you’ll:

• Partner with Product and BI to translate business goals into well-scoped modelling problems, with clear success criteria and guardrails.
• Build and productionize models across areas such as customer segmentation, lifetime value, churn and retention, and personalised recommendations.
• Design evaluation datasets, offline benchmarks, and online feedback loops so model quality is measured, not assumed.
• Work with engineering on how model outputs are surfaced — latency, payload design, fallback behaviour, and failure modes are part of the job.
• Monitor deployed models for drift and performance over time; own the retraining and improvement cadence.
• Translate user feedback and product telemetry into concrete model and feature improvements.
• Build alongside coding agents — drive agentic loops to scaffold pipelines, write and refactor production code, generate tests, and accelerate exploratory analysis, while keeping a human-in-the-loop for design and review decisions.
• Communicate results and trade-offs clearly to technical and non-technical audiences.

You might be a great fit if you:

• 5+ years of experience as a Data Scientist, Applied Scientist, or ML Engineer shipping production models in a commercial software environment.
• Expert-level SQL and Python, and comfort working with modern cloud data warehouses.
• Production experience with at least two of: customer segmentation, churn or propensity modelling, lifetime value, or recommender systems.
• A disciplined approach to evaluation — you define metrics up front, understand baselines, and guard against data leakage and overfitting.
• Experience serving model outputs through APIs consumed by a product UI.
• Hands-on fluency with coding agents (e.g., Claude Code, Cursor, Copilot agents, or similar) and genuine comfort operating in agentic loops — you can plan, prompt, review, iterate, and ship using agents as part of your everyday workflow.
• A builder’s instinct for AI-assisted development: you know how to structure context, write clear specs, decompose work into agent-sized tasks, and verify outputs rigorously.
• Clear written and verbal communication; you can defend a model choice and explain a result to someone who is not a data scientist.

Bonus points if you:

• Have experience in loyalty, CRM, retail analytics, or related industries
• Have worked with LLM-assisted analytics or conversational data systems
• Have experience building custom AI agents, tools, MCP servers, or evaluating agent performance on real task
• Are bilingual in English and French

If you’re excited about building intelligent systems that combine machine learning, product thinking, and AI-assisted development to create experiences that feel genuinely impactful—we’d love to meet you.