Lead Product Analyst - Operations

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 and what we offer.

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’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.
• 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.
• Strategic Support and Analysis: Provide critical insights to assess the operational health of the KYC 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.

This is an IC3 role. For more information on our Analytics Career Map and levelling structure, click here.

What you'll bring:

• You have 6 - 8 years of experience in analytics with a demonstrated ability to approach complex, interconnected problems with a systems mindset.
• You have a strong quantitative and statistical background, comfortable with probability, hypothesis testing, regression, time series analysis, and thinking in terms of models and trade-offs.
• You have experience with operational analytics: efficiency analysis, cost modelling, performance measurement, or process optimisation.
• You think about data as infrastructure. You build with reusability and quality in mind, considering how data will be consumed by dashboards, other teams, and automated systems.
• You have experience with complex data models in SQL (our warehouse is Snowflake) and advanced analysis using Python/R.
• You can tell a story with data and proactively guide strategy based on insights. Experience with visualisation tools like Looker, Superset, or Tableau.
• You have a bias to action and are an excellent communicator, able to own projects end-to-end, form your own opinions, and influence stakeholders across teams.

Some extra skills that are great (but not essential):

• Experience with optimisation problems such as queuing theory, scheduling, or resource allocation.
• Familiarity with forecasting techniques (ARIMA, Holt-Winters, or similar time series methods).
• Experience building data foundations that support ML/AI - feature engineering, labelled datasets, or structured event data.
• Prior experience in operations, servicing, or compliance domains.
• Familiarity with workforce management, quality assurance, or knowledge management analytics.
• Experience with dbt, Airflow, or Git.

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.

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