Drive data-driven decisions in operational teams for a global technology company while optimizing processes and enhancing customer experiences.
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 be driving our analytics efforts in our operations teams, who do everything from support our customers when they need help, to screening for criminal activity, to verifying customer identities at scale.
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 will be contributing:
This is an IC3 role. For more information on our Analytics Career Map and levelling structure, click here.
What you will 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.
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.
Wise is a global technology company focused on making money movement and management seamless for individuals and businesses. By facilitating international payments and cross-border transactions, Wise aims to simplify financial interactions and significantly reduce costs associated with sending and receiving money worldwide.
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Lead Data Analyst Q&A's