At a Glance
- Tasks: Lead data analysis to drive operational improvements and enhance customer experiences.
- Company: Wise, a global tech company revolutionising money management.
- Benefits: Inclusive culture, competitive salary, and opportunities for career growth.
- Other info: Diverse and inclusive environment fostering innovation and collaboration.
- Why this job: Join a mission-driven team making money accessible for everyone, everywhere.
- Qualifications: 4+ years in analytics with strong statistical and data visualisation skills.
The predicted salary is between 60000 - 80000 £ per year.
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.
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 enhance decision-making and strategic planning.
- Causal 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.
- Strategic 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.
- Performance Tracking and Initiative Optimisation: Monitor and track the performance of key strategic initiatives, capitalising on optimisation opportunities to enhance operational outcomes.
- KPI 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.
- Stakeholder 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.
WHAT YOU’LL BRING:
- Quantitative 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.
- A 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.
- You 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.
- You have a background working with operational team analytics including capacity planning, forecasting, efficiency analysis, quality assurance, predictive analytics, and experimentation.
- You have experience working with complex data models in SQL (our warehouse is Snowflake) and analysing it using advanced SQL/Python/R able to demonstrate that you can tell a story and proactively give guidance on strategy based on insights.
- You have experience with data visualisation tools (Looker, PowerBI, Tableau etc.) and demonstrate storytelling ability with data.
- You have a bias to action - you identify what needs to be done and make it happen.
Some extra skills that are great (but not essential):
- Prior experience in Operation domains.
- You have experience working with a WFM or Quality team.
- You have experience working with WFM Systems.
- You have experience with forecasting techniques such as ARIMA, Holt-Winters, and other time series analysis methods.
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. We're proud to have a truly international team, and we celebrate our differences. Inclusive 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.
If you want to find out more about what it's like to work at Wise visit Wise.Jobs. Keep up to date with life at Wise by following us on LinkedIn and Instagram.
Lead Analyst - Total Service (Operations) in London employer: Wise
Wise is an exceptional employer that champions a diverse and inclusive work culture, empowering employees to contribute meaningfully to our mission of Money Without Borders. With a strong focus on professional growth, we offer ample opportunities for career advancement and skill development, all while working in a dynamic environment that values innovation and collaboration. Located in a vibrant city, our team enjoys a flexible work-life balance and the chance to be part of a global movement that is transforming the way money is managed worldwide.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Analyst - Total Service (Operations) in London
✨Tip Number 1
Network like a pro! Reach out to current employees at Wise on LinkedIn and ask them about their experiences. A friendly chat can give you insider info and might even lead to a referral!
✨Tip Number 2
Prepare for the interview by diving deep into Wise's mission and values. Show us how your skills align with our goal of Money Without Borders, and be ready to discuss how you can contribute to our operations.
✨Tip Number 3
Practice your data storytelling! We love candidates who can take complex data and turn it into actionable insights. Use examples from your past work to demonstrate how you've done this before.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team.
We think you need these skills to ace Lead Analyst - Total Service (Operations) in London
Some tips for your application 🫡
Show Your Passion:When you're writing your application, let your enthusiasm for our mission of Money Without Borders shine through. We want to see how you connect with our goals and how you can contribute to making money management easier for everyone.
Tailor Your Experience:Make sure to highlight your relevant experience in analytics and operations. We love seeing how your background aligns with the role, so don’t be shy about showcasing your skills in capacity planning, forecasting, and data analysis.
Be Clear and Concise:Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon and focus on communicating your ideas effectively. Remember, we’re looking for someone who can simplify complex data into actionable insights!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about what we do at Wise!
How to prepare for a job interview at Wise
✨Know Your Data Inside Out
As a Lead Data Analyst, you'll be expected to have a solid grasp of data models and analytics. Brush up on your SQL skills and be ready to discuss how you've used data to drive decisions in past roles. Prepare examples that showcase your ability to separate signal from noise in complex datasets.
✨Showcase Your Problem-Solving Skills
Be prepared to tackle hypothetical scenarios during the interview. Think about how you would approach capacity planning or predictive modelling challenges. Use the STAR method (Situation, Task, Action, Result) to structure your responses and highlight your strategic mindset.
✨Collaborate Like a Pro
Collaboration is key in this role. Be ready to discuss how you've worked with cross-functional teams in the past. Share specific examples of how your insights led to operational improvements and how you’ve standardised processes across teams.
✨Understand Wise's Mission
Familiarise yourself with Wise's mission of 'Money Without Borders'. Be prepared to articulate how your skills and experiences align with this mission. Show enthusiasm for the company's goals and be ready to discuss how you can contribute to making money management easier for everyone.