At a Glance
- Tasks: Drive data-driven decisions to optimise customer operations and enhance service quality.
- Company: Join Wise, a global tech company revolutionising money management.
- Benefits: Competitive salary, inclusive culture, and opportunities for career growth.
- Other info: Diverse and inclusive team environment with a focus on personal development.
- Why this job: Make a real impact on how the world manages money with innovative analytics.
- Qualifications: 4+ years in analytics, strong statistical skills, and experience with SQL/Python.
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. As part of our team, you will be helping us create an entirely new network for the world's money. For everyone, everywhere.
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 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) employer: Wise
Wise is an exceptional employer that champions a culture of inclusivity and innovation, making it an ideal place for a Lead Analyst in Total Service Operations. With a commitment to employee growth, you will have access to diverse opportunities for professional development while working alongside a global team dedicated to transforming the way money moves across borders. Enjoy a dynamic work environment that values data-driven decision-making and fosters collaboration, ensuring your contributions directly impact our mission of Money Without Borders.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Analyst - Total Service (Operations)
✨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 maybe even 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 making money management easier for everyone. We love candidates who are genuinely passionate!
✨Tip Number 3
Practice your storytelling skills! When discussing your past experiences, frame them in a way that highlights your analytical prowess and how you've driven operational improvements. We want to see how you think!
✨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 us you’re serious about joining the Wise team!
We think you need these skills to ace Lead Analyst - Total Service (Operations)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Lead Analyst role. Highlight your experience in analytics, especially in operational contexts, and showcase any relevant projects that demonstrate your skills in data-driven decision-making.
Craft a Compelling Cover Letter:Your cover letter is your chance to tell us why you're passionate about our mission of Money Without Borders. Share specific examples of how you've used data to drive improvements in previous roles and how you can bring that expertise to Wise.
Showcase Your Analytical Skills:In your application, don't just list your skills—show us how you've applied them! Use concrete examples to illustrate your experience with predictive modelling, capacity planning, and any tools like SQL or Python that you've mastered.
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 our culture and values!
How to prepare for a job interview at Wise
✨Know Your Numbers
As a Lead Data Analyst, you'll be expected to have a strong grasp of data. Brush up on your statistics and analytics skills before the interview. Be ready to discuss how you've used data to drive decisions in past roles, and prepare examples that showcase your ability to separate signal from noise.
✨Showcase Your Storytelling Skills
Data isn't just about numbers; it's about the story they tell. Prepare to explain complex data insights in a way that's easy to understand. Use visualisation tools like Tableau or PowerBI to demonstrate how you can turn raw data into actionable insights that impact operational outcomes.
✨Understand the Business
Familiarise yourself with Wise's mission and how it operates. Understand the challenges they face in customer operations and think about how your analytical skills can help solve these issues. This will show your genuine interest in the role and the company.
✨Prepare for Technical Questions
Expect questions around SQL, Python, and predictive modelling techniques. Brush up on your knowledge of data pipelines and forecasting methods. Be prepared to discuss specific projects where you've applied these skills, and don't hesitate to share any innovative solutions you've implemented.