Lead Data Analyst - Total Service (Operations) (London)
Job Description
hackajob is collaborating with Wise to connect them with exceptional professionals for this role.
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Company Description
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Wise is a global technology company, building the best way to move and manage the world’s money.
\nMin fees. Max ease. Full speed.
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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.
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As part of our team, you will be helping us create an entirely new network for the world's money.
\nFor everyone, everywhere.
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More about our mission and what we offer.
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Job Description
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THE ROLE
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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.
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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
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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!
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Here’s how you’ll be contributing:
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- \nAnalytical 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.\n
- \nData 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.\n
- \nPredictive 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 enhance decision-making and strategic planning.\n
- \nCausal Inference and Quasi-Experimental Analysis. Develop robust approaches to cause-and-effect analysis in an environment where A/B testing is potentially feasible - applying techniques such as difference-in-differences, regression discontinuity, or synthetic controls to evaluate the true impact of servicing interventions and confidently attribute outcomes without waiting for ideal conditions.\n
- \nStrategic Support and Analysis. Provide critical insights to assess the operational health of the Total Services function, conduct in-depth cost analysis, and offer detailed analysis of operational metrics (including quality) to understand impacts on customer experiences.\n
- \nPerformance Tracking and Initiative Optimisation. Monitor and track the performance of key strategic initiatives, capitalising on optimisation opportunities to enhance operational outcomes.\n
- \nKPI Implementation and Target Setting. Lead the development and implementation of the operations KPI tree and the target-setting framework, integrating these within reporting pipelines and strategic operations.\n
- \nStakeholder Collaboration and Process Standardisation. Collaborate closely with various stakeholders to standardise processes across forecasting, scheduling, and real-time operations, promoting continuous improvement and strategic alignment.\n
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This is an IC3 role. For more information on our Analytics Career Map and levelling structure, click here.
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Qualifications
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WHAT YOU’LL BRING
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- \nQuantitative Foundation. Ideally, you have a background in statistics, maths, physics, engineering, economics, or another scientific field. You apply first-principles thinking to break down complex operational problems.\n
- \nA Statistical Mindset. You have a natural grasp of data logic. You don't just look at averages; you understand distributions, variance, and significance. You enjoy applying that rigor to messy, real-world operational data to separate signal from noise.\n
- \nYou have 4+ years of experience in analytics with demonstrated ability to approach complex problems with a strategic mindset, identifying innovative solutions that drive operational improvements.\n
- \nYou have a background working with operational team analytics including capacity planning, forecasting, efficiency analysis, quality assurance, predictive analytics, and experimentation.\n
- \nYou have experience working with complex data models in SQL (our warehouse is Snowflake) and analysing it using advanced SQL/Python/R\n
- \nAble to demonstrate that you can tell a story and proactively give guidance on strategy based on insights\n
- \nYou have experience with data visualisation tools (Looker, PowerBI, Tableau etc.) and demonstrate storytelling ability with data\n
- \nYou have a bias to action - you identify what needs to be done and make it happen.\n
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Some extra skills that are great (but not essential):
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- \nPrior experience in Operation domains\n
- \nYou have experience working with a WFM or Quality team.\n
- \nYou have experience working with WFM Systems\n
- \nYou have experience with forecasting techniques such as ARIMA, Holt-Winters, and other time series analysis methods\n
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Additional Information
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For everyone, everywhere. We're people building money without borders — without judgement or prejudice, too. We believe teams are strongest when they are diverse, equitable and inclusive.
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We're proud to have a truly international team, and we celebrate our differences.
\nInclusive teams help us live our values and make sure every Wiser feels respected, empowered to contribute towards our mission and able to progress in their careers.
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If you want to find out more about what it's like to work at Wise visit Wise.Jobs.
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Keep up to date with life at Wise by following us on LinkedIn and Instagram.