Wise

Financial Technology

LeadAnalyst-TotalService(Operations)

£85–125k ~AI est. London, United Kingdom FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for mid candidates.

The Brief

“Lead Analyst - Total Service (Operations) at Wise. Skills: Capacity planning, Forecasting, Predictive modeling, Causal inference. Build and refine analytical models for capacity planning. Take ownership of forecasting efforts”

What You'll Achieve.

Drive data-driven decisions; Scale what works; Improve how we resolve customer issues; Enhance decision-making; Enhance strategic planning; Attribute outcomes without waiting for ideal conditions; Enhance operational outcomes

Industry & Context.

Financial Technology
Problems you'll solve

Break down complex operational problems; Separate signal from noise

What They're Looking For.

Must Have

4+ years of experience in analytics, Background working with operational team analytics, Experience working with complex data models in SQL, Experience analysing data using advanced SQL/Python/R, Experience with data visualisation tools, Demonstrated storytelling ability with data

Nice to Have

Prior experience in Operation domains, Experience working with a WFM or Quality team, Experience working with WFM Systems, Experience with forecasting techniques such as ARIMA, Holt-Winters, and other time series analysis methods

What You'll Do.

Build and refine analytical models for capacity planning

Take ownership of forecasting efforts

Maintain and improve data flow

Develop and implement robust models to predict outcomes

Perform cause and effect analysis

Provide critical insights to assess operational health

Conduct in-depth cost analysis

Offer detailed analysis of operational metrics

Monitor and track performance of key strategic initiatives

Capitalise on optimisation opportunities

Lead development and implementation of operations KPI tree

Lead development and implementation of target-setting framework

Integrate KPIs and target setting within reporting pipelines

Collaborate closely with stakeholders

Standardise processes across forecasting

and real-time operations

How You'll Work.

Team & Collaboration

Operational teams; Workforce management; Quality; Training; Knowledge management; Operational leads

Communication Scope

Storytelling with data

Full Job Description

Wise is a global technology company, building the best way to move and manage the world’s money. Min fees. Max ease. Full speed. Whether people and businesses are sending money to another country, spending abroad, or making and receiving international payments, Wise is on a mission to make their lives easier and save them money. As part of our team, you will be helping us create an entirely new network for the world's money. For everyone, everywhere. More about [our mission](https://wise.jobs/our-mission) and [what we offer](https://wise.jobs/what-we-offer). THE ROLE We’re looking for a Lead Data Analyst who is passionate about our mission of Money Without Borders to partner with our operational teams to help drive data-driven decisions that would support our fast-growing product through scaling and optimising the team. As a Lead Data Analyst, you’ll drive analytics within a dedicated customer operations model where we improve how we resolve complex and time‑sensitive customer issues—speed, reliability, quality, and end‑to‑end outcomes—and scale what works across our wider Operations teams Most importantly, you’ll collaborate closely with your operational leads, as well as workforce management, quality, training, and knowledge management, to bring your insights into real change for our customers and help drive our mission! Here’s how you’ll be contributing: * Analytical Capacity Planning and Forecasting. Focus on building and refining analytical models for strategic capacity planning. Take ownership of forecasting efforts to align with business growth and operational demands. * Data Pipeline Ownership. Take ownership of data pipelines to maintain and improve data flow, ensuring reliability and accuracy of data that drives high-stakes servicing interventions at scale. * Predictive Modeling and Cause and Effect Analysis. Develop and implement robust models to predict outcomes and perform cause and effect analysis to identify key drivers, optimise processes, and enhanc

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