Analytics & Intelligence Engineer

Our client is a Singapore-headquartered AI-native data & service platform delivering cyber, digital, and risk solutions across Asia. They help essential service enterprises make responsible decisions through the collective intelligence of humans and machines.

AI is embedded in how they build and run systems, but humans remain accountable.

We're looking for an Analytics & Intelligence Engineer to help deliver accurate, trusted insights that drive real-world outcomes. This role sits at the intersection of data, reporting, operational decision-making, and narrative clarity — ensuring stakeholders don't just see the numbers, but understand what they mean.

This is a role for someone who cares deeply about metrics correctness, interpretation, and the quality of the story data tells.

As an Analytics & Intelligence Engineer, you will own:

• Metrics, reporting, and narrative correctness

• Interpretation and explanation of outcomes

• Clear communication of insights, including uncertainty where it exists

• Continuous improvement of reporting reliability and trust

Your build focus is Service, meaning you contribute to domain intelligence where outcomes are defined — such as Fraud, SecOps, Asset Intelligence, or other business-critical service areas.

This focus defines your long-term ownership: the analytics capability that supports real operational decisions.

Your run focus is Present, meaning your work directly supports how outcomes are delivered, explained, and consumed.

You ensure reporting outputs are not only accurate, but understandable and decision-ready.

In this role, you will:

• Build and maintain reporting solutions that deliver accurate, reliable metrics

• Design, validate, and improve analytics logic that supports operational outcomes

• Investigate anomalies and inconsistencies in reporting outputs and underlying datasets

• Translate complex data into clear narratives that stakeholders can act on

• Create explanations that help teams understand why outcomes occurred, not just what happened

• Collaborate with engineers, analysts, and domain teams to ensure alignment on metric definitions and reporting intent

• Own the correctness of dashboards, reports, and insights delivered to end users

• Apply validation and quality checks before reports are released or consumed

• Document metric definitions, assumptions, and limitations to ensure transparency and long-term trust

We use AI as a productivity accelerator — not as a decision-maker.

You will use AI to:

• Generate and refine queries

• Draft reports, summaries, and narratives

• Detect anomalies and inconsistencies

• Explore edge cases and propose explanations

However, AI never owns outcomes. Humans do.
You will review, validate, and be accountable for what is ultimately communicated.

This role participates in CI/CD practices to ensure analytics outputs are safe and correct.

You will:

• Contribute to CI pipelines for analytics logic, testing, and validation

• Validate reports before release

• Participate in release readiness by ensuring that reporting quality gates are met

You will not own deployment mechanics, but you are expected to work effectively within a CI/CD environment.

We design systems where judgment is not optional.

You will be responsible for:

• Reviewing AI-generated insights before they are published or shared

• Ensuring accuracy of metrics and narratives

• Communicating uncertainty clearly when inputs or outcomes are ambiguous

• Owning the downstream impact of reporting and interpretation

We're looking for someone who has:

• Experience working with analytics, reporting, dashboards, or data pipelines

• Strong SQL skills and the ability to write clear, maintainable queries

• Understanding of metrics design, validation, and data quality principles

• Ability to explain outcomes clearly to both technical and non-technical stakeholders

• Strong attention to detail and a high bar for correctness

• Comfort working in environments where AI is used as an assistive tool (with human accountability)

• Familiarity with CI practices such as testing, validation checks, and review workflows

• A mindset focused on trust, transparency, and continuous improvement

Bonus points if you have experience with:

• Python or another language used for analytics automation

• BI tools (e.g., Looker, Power BI, Tableau, Mode, Metabase)

• Data transformation frameworks (e.g., dbt)

• Monitoring and anomaly detection techniques

• Working in operational domains such as Fraud, Risk, Compliance, Security, or Asset Intelligence

• Writing documentation and metric definitions for long-term reuse

Success in this role means:

• Reports and dashboards remain correct, stable, and trusted

• Stakeholders receive clear narratives, not just raw metrics

• Anomalies are detected early, investigated quickly, and explained confidently

• Analytics outputs are delivered safely through validation gates

• Data becomes a tool for decision-making, not confusion

We believe analytics is not just about building dashboards - it's about delivering truth, clarity, and confidence in high-impact environments.

If you care about correctness, communication, and building intelligence that drives real outcomes, we'd love to hear from you.