Senior Data Analyst - Onboarding

About The Company

Founders today are building global companies from day one — but the systems that manage their money were built for a different era. Aspire exists to change that!

We’re building the financial operating system for global founders, bringing banking, software, and automation into a single platform so businesses can move faster across borders and stay focused on building.

Aspire is built by people who think from first principles, care deeply about solving hard problems, and take real ownership of their work. Our team brings global experience from leading fintech and technology companies, and many of us are former founders and operators who understand what it takes to build thoughtfully, make trade-offs, and deliver at scale in a global environment.

Backed by leading global investors including Y Combinator, Peak XV, and Lightspeed, Aspire has been trusted by more than 50,000 startups and growing businesses worldwide to manage their finances since 2018. Together with partners like J.P. Morgan, Visa, and Wise, we’re building for the next generation of global companies.

About The Role

At Aspire, we are committed to empowering our customers throughout their journey with us. Our Operations Team ensures customers can operate seamlessly on our platform and guarantees the best customer experience possible. The Onboarding team performs KYB and KYC on our leads. We aim to review applications as fast as possible while maintaining strong risk standards, so every new business gets a seamless start with Aspire.

Responsibilities

As a Senior Data Analyst for Onboarding, you will be the analytical backbone of how Aspire brings new businesses onto the platform, balancing speed, customer experience, and risk. Your responsibilities will include:

• Own Onboarding Metrics & Reporting: Define, validate, and continuously refine the core KPIs for onboarding, such as application-to-approval conversion, time-to-decision, SLA adherence, drop-off rates, and approval/rejection rates by market and segment. Maintain reporting that reflects the latest performance across all markets.
• Optimise the Onboarding Funnel: Dive deep into the end-to-end applicant journey to pinpoint where businesses drop off or stall, and partner with Product and Growth to design and measure experiments that improve conversion without compromising risk controls.
• Build Data Science Models for Smarter Onboarding: Develop and deploy predictive models for applicant risk assessment, client prioritisation, and review-queue routing, so high-value and low-risk businesses move through faster while higher-risk cases get the right level of scrutiny. Partner with FinCrime, Compliance, and Engineering to validate model performance, monitor for drift, and keep decisions explainable to reviewers and regulators.
• Measure Decision Quality & Risk: Track the quality of KYB/KYC decisions, including rework rates, false positives in screening, manual review rates, and post-onboarding risk signals, working with FinCrime and Compliance to keep our risk appetite and our customer experience in balance.
• Support New Market & Product Launches: Set up onboarding performance tracking for new markets, entity types, and products from day one, so the team can see how new flows perform and course-correct quickly
• Mine Insights for Impact: Dig into operational and customer data to uncover trends and deliver recommendations that improve efficiency, conversion, and the quality of the businesses we onboard.
• Drive Volume & Capacity Forecasting: Build and maintain models that forecast application volumes, review backlog, and analyst capacity needs, helping leadership plan headcount and resourcing ahead of demand spikes
• Build Scalable Dashboards & Self-Serve Analytics: Design and enhance dashboards that let Onboarding leads, Ops managers, and cross-functional stakeholders answer their own questions, and handle ad-hoc data requests with speed and rigour.
• Automate & Apply AI: Automate recurring reporting, optimise data pipelines, and identify opportunities where rules, models, or AI tools can reduce manual review effort and speed up decisions.
• Collaborate Cross-Functionally: Partner with Onboarding, Product, Engineering, FinCrime, Compliance, and Sales to translate business needs into clear data solutions and recommendations.

Minimum Qualifications

• A minimum of 4 years of experience in data analytics, ideally in operations, risk, or onboarding analytics within fintech, banking, or financial services.
• Advanced proficiency in SQL for extracting, manipulating, and analysing large datasets, plus experience with at least one BI tool (e.g. Tableau, Looker, or Databricks dashboards)
• Has a strong grasp of artificial intelligence concepts and the ability to apply AI tools and frameworks to solve real world problems at Aspire.
• Proven track record of building funnel, operational, or capacity metrics and turning them into decisions that measurably improved performance.
• Strong communication skills, with the ability to translate complex analysis into clear recommendations for both operational and senior stakeholders.

Preferred Qualifications

• Working knowledge of Funnel analytics, and some onboarding journeys like KYB/C, AML, and customer due diligence processes, including how screening and verification vendors work.
• Experience with Python (or R) for analysis, automation, or forecasting.
• Experience with A/B testing or experimentation design on customer-facing flows.
• Hands-on experience building and deploying predictive models (e.g. classification, risk scoring, prioritisation) in Python using libraries such as scikit-learn, XGBoost, or similar
• Solid grounding in statistics and model evaluation, including feature engineering, handling imbalanced data, and metrics like precision/recall and AUC.
• Exposure to multi-market operations across APAC, the US, or Europe, and the regulatory differences that shape onboarding in each.
• A proactive, ownership-driven mindset and the ability to juggle multiple projects and stakeholders in a fast-paced, high-growth environment.

By submitting this application, I confirm that all the information given by me in this application for employment and any additional documents attached hereto are true to the best of my knowledge and that I have not wilfully suppressed any material fact. I confirm I have disclosed if applicable any previous employment with Aspire. I accept that if any of the information given by me in this application is in any way false or incorrect, my application may be rejected, any offer of employment may be withdrawn or my employment with Aspire may be terminated summarily or I may be dismissed. By submitting this application, I agree that my personal data will be processed in accordance with Aspire's Candidate Privacy Notice.