Wise · Hyderabad, India

Lead Product Analyst - Operations

Hyderabad, IndiaFull-timeManager or leadOperations

Listed on Wise’s official careers site. Posted October 30, 2026. Check that it is still open and apply there.

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Job description

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 .

Qualifications

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.

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