Automation Senior Analyst

We are looking for an Automation Senior Analyst to join our Spend Automation team in Singapore. This is a technical IC role for someone who wants to use data, coding, automation rules, and LLMs to improve how Wise handles card disputes at scale.

You will help find the highest-impact automation opportunities, turn them into safe and measurable automation logic, and build the feedback loops that tell us whether automation is working for customers, Operations, and Wise.

Your mission: 

Wise has already pioneered new ways for people to transfer money across borders and currencies. Our customers can also manage their hard-earned money with the world’s first platform to offer true multi-currency banking, and they can spend every day using our Wise debit card. 

The Spend OPS team is part of Spend squad whose mission is: reliable, convenient & eventually free to spend anywhere in the world;  

By now, we have a well organised operational team, who work very closely with our dedicated engineering and product teams, across offices in three continents. We partner with the card schemes and other relevant product, engineering and operational teams in Wise, to get things done. 

As an Automation Senior Analyst, you will be the technical owner for automation across Wise's card dispute operations. You will use code, automation rules, and LLMs to automate operational workflows. You will work closely with domain specialists, Product, Engineering, Data Science, Analytics, and Dispute Operations to move ideas from discovery to live, measured impact.

This role is not about producing reports on request. It is about owning the technical path from problem to automation.

Automation Discovery And Pattern Mining

• Analyse card dispute and operational data to identify patterns, gaps, edge cases, and root causes that point to automation opportunities.

• Use SQL and Python or similar scripting to run deep dives, size opportunities, and separate high-value patterns from noise.

• Build clear business cases using handling time, automation rate, decision quality, customer impact, and operational risk.

• Stay close to fraud and non-fraud dispute workflows so technical recommendations reflect how cases actually behave in practice.

Automation Rules And Decision Logic

• Own the design, writing, testing, and improvement of automation rules and decision logic.

• Define clear rule conditions, exclusions, guardrails, fallback paths, and monitoring needs.

• Improve current automation-rule precision, coverage, and maintainability.

LLM And AI-Assisted Automation

• Own practical LLM-assisted automation use cases across card disputes.

• Work with prompts, structured outputs, task definitions, confidence thresholds, and failure analysis.

• Review model outputs against human decisions or labelled examples to understand where the LLM is strong, where it fails, and what should change next.

• Partner with Data Science, Product, and Engineering to decide when an LLM use case is ready to pilot, when it needs narrowing, and when it should stop.

• Use LL Ms as part of safe automation workflows, not as a shortcut around operational judgement.

Qualifications

About You

• You have strong SQL and python skills and can work confidently with complex operational datasets.

• You are familiar with LLMs and excited by practical AI-assisted automation. You do not need to be a machine learning researcher, but you should understand prompts, structured outputs, failure modes, and why evaluation matters.

• You are comfortable writing or learning to write automation rules.

• You can build dashboards or monitoring views that help teams make better decisions.

• You think clearly from data, but you do not stop at analysis. You turn findings into action.

• You are comfortable with ambiguity and can move work forward without needing step-by-step instructions.

• You care about customer outcomes and understand that automation needs to be correct, explainable, and safe.

• You communicate clearly with both technical and non-technical stakeholders.

• You enjoy coaching peers and helping others become stronger technical thinkers.

Nice To Have

• Experience in fraud, risk, FinCrime, payments, card disputes, chargebacks, or operational automation.

• Experience with rule engines, risk engines, workflow automation, or decision systems.

• Experience with control groups, A/B tests, pre/post analysis, or operational quality measurement.