Senior Commercial Analyst

About the role

Wise is a global technology company building the best way to move and manage the world's money — min fees, max ease, full speed. Wise Platform takes all of the world-class payments products Wise has built over the last 15 years and enables hundreds of millions of consumers and businesses to access them in the places where they already move and manage their money, with banks and online platforms. Today Wise Platform powers payments for top neobanks like Monzo, N26, and Nubank, leading global banks such as UniCredit, Morgan Stanley, and Standard Chartered, and online platforms including Google, Agoda, Upwork, Deel, and Interactive Brokers.

We're looking for a Senior Regional Analyst (Northam) to join our deal-flow analytics team in Wise Platform. You will partner with our Commercial and Delivery teams based in North America, empowering them with data and insights to drive growth. Your analysis and sales intelligence will enable us to optimise sales and delivery processes, reduce time to revenue, and drive team performance.

Responsibilities

• Deliver high-impact, scalable data solutions: build and maintain robust reporting models and data products that directly support the sales and delivery team's efficiency and effectiveness.
• Design and implement key performance indicators (KPIs) for commercial and delivery teams, with a laser focus on revenue as a core metric, ensuring clear measurement and understanding of team performance, alongside providing actionable recommendations to drive commercial objectives.
• Leverage advanced analytics to craft dashboards and visualisations that bring commercial performance data to life, tell a clear story, and offer diagnostic power:
  • For the Sales Team: analyse sales pipeline health, deal velocity, stage conversion rates, and win/loss reasons; build reports to track individual sales representative performance against quotas, identify top performers, and pinpoint areas for improvement, leveraging Salesforce's opportunity management, forecasting, and activity tracking features.
  • For the Pre-Sales Team: monitor engagement metrics (e.g., number of RFIs, technical discussions), the impact of pre-sales activities on deal progression and win rates, and the efficiency of their resource allocation; create visibility into their contribution to the sales cycle and quantify their impact.
  • For the Implementation/Delivery Team: track, monitor, and predict key metrics and data points across the project lifecycle; work with the team to identify risks and opportunities to improve the speed and quality of implementations, reducing time to revenue and successfully scaling solutions with partners.
• Collaborate with analysts in the team to enhance forecasting capabilities, enabling performance management of the business, teams, and partners, and supporting operational teams to capacity plan effectively.
• Shape how we leverage data to sell Wise Platform, identifying key insights and crafting compelling data-driven narratives that empower commercial teams to convert prospects into partners.

Requirements

• Proficient with SQL and experienced with data pipeline management tools such as Snowflake, dbt, Git, Airflow, Python, and Looker; comfortable owning analytics from data transformation through to delivering actionable insights.
• Commercially minded: able to translate analysis into impact and comfortable with opportunity sizing, forecasting, and scenario modelling.
• Experience working in a high-growth B2B tech environment and working closely with commercial teams.
• Solution-oriented, able to own projects from start to finish; comfortable motivating stakeholders across Wise and negotiating timelines to unblock yourself and make things happen.
• Excellent communicator, able to form your own opinions and effectively articulate them to win colleagues round to your way of thinking; comfortable writing and maintaining clear and concise documentation.

Preferred qualifications

• Experience working with sales and project management data in tools like Salesforce or similar.
• Proficient in Python's data transformation, visualisation, and statistics libraries (e.g., pandas, numpy, scipy, plotly).
• Experience working with payments or transactions data.