Data Scientist - Financial Crime

At Aspire, we’re more than just a FinTech company—we’re the leading all-in-one financial operating system built to empower the world’s innovators and entrepreneurs. We are on a mission to reinvent business finance, empowering startups and businesses to realise their full potential.

Founded in 2018, Aspire has raised over USD 300M+ across equity and debt from world-class investors. In 2023, we successfully closed an oversubscribed USD 100 million Series C equity round led by Sequoia Capital and Lightspeed Ventures with participation of Tencent, Paypal Ventures, LGT Capital Partners, Picus Capital and MassMutual Ventures. To power our solutions, we have partnered with some of the best companies in the world such as Visa and Wise and empowered more than 50,000 businesses using our suite of products.

Aspire has consistently been recognized for excellence, earning Best Employer and Startup of the Year by the Asia FinTech Awards in 2022 and 2023, ranked as LinkedIn’s Top Startup in Singapore, and listed on CB Insights’ Top 100 Global Fintech in 2023 and 2024.

You will be amazed by the energy and experience of our team! Aspire serves as an environment for you to innovate and drive change with our team of ex-entrepreneurs, ex-founders, and high-achievers with international and diverse backgrounds.

Are you a top talent who is passionate about entrepreneurship? Join our rapidly growing team to make an impact in the fintech space! 

About the role:

The Data Scientist will be responsible for using advanced analytics techniques to identify suspicious patterns, assess control effectiveness, and recommend enhancements to mitigate financial crime risks, delivering against our ambition to become a truly data-led function using cutting-edge systems and technologies to prevent financial crime. The Data Scientist will leverage knowledge of financial crime typologies and threats to conduct advanced analysis of both internal and external data for the purpose of deriving the most effective mitigation strategies, which can be implemented through our systems and processes. The Data Scientist will have experience of using advanced analytics techniques (complex modelling, machine learning) to extract insights from the available data and propose effective mitigation strategies (such as risk indicators, rules, or process changes). The Data Scientist will work closely with the Product, Engineering, Data and Operations teams to implement these strategies, monitor their effectiveness and continuously improve them. 

Key Responsibilities:

• Data Analysis & Insights: Analyze large volumes of transaction and customer data to identify anomalies and patterns indicative of financial crime.
• Risk Assessment: Evaluate existing financial crime systems controls and provide data-driven insights on their effectiveness.
• System calibration and testing: Support the set up and ongoing calibration of rules in our systems and test their effectiveness
• Model Development: Build and refine predictive models for fraud detection, money laundering risk scoring, and suspicious activity monitoring.
• Control Optimization: Recommend and implement data-driven enhancements to AML and fraud detection systems, ensuring they are efficient and effective.
• Machine Learning & AI: Develop machine learning algorithms to improve fraud detection capabilities, reduce false positives, and enhance efficiency
• Collaboration & Communication: Work closely with operations, product and data teams to translate data insights into actionable strategies.
• Regulatory Compliance: Ensure that models and analytical approaches align with AML/CTF regulations and industry best practices.

Key Requirements:

Essential Skills & Experience:

• Proven experience (5+ years) as a Data Scientist, Financial Crime Analyst, or Risk Analyst in a financial institution, fintech, or regulatory environment.
• Strong expertise in Python, R, SQL, and big data technologies for data analysis and modeling.
• Experience in machine learning, anomaly detection, and statistical modeling applied to financial crime risk mitigation.
• Familiarity with fraud detection techniques, AML monitoring systems, and regulatory frameworks 
• Experience working with transactional, behavioral, and network data to detect suspicious activities.
• Strong problem-solving skills with the ability to derive meaningful insights from complex datasets.
• Excellent communication skills to explain technical findings to non-technical stakeholders.

Preferred Skills & Qualifications:

• Familiarity with Sardine.ai or similar financial crime detection systems
• Experience with graph analytics and network analysis for identifying financial crime patterns.

What we offer

• Uncapped flexible annual leave.
• Hybrid work arrangement. 
• Training subsidy for your professional growth.
• Wellness benefit.
• Team bonding budget to foster collaboration and sense of belonging.
• Flexibility to work from anywhere (for up to 90 days per annum).
• Culture is Key: We always strive to cultivate a special culture that brings special talents together - You can learn more about our culture on our careers site and LinkedIn Life page.
  

Equal Opportunity Statement 

Aspire is an equal opportunity employer and is committed to providing equal employment opportunities to all qualified individuals without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or any other protected characteristic as outlined by applicable laws. 

Please note: by submitting your application, you acknowledge that you have read and understood Aspire’s Data Protection Policy for Employees, Freelancers, Contractors and Job Applicants (the “Policy”), and consent to the collection, use and disclosure of your personal data by Aspire for the purposes set out in the Policy. You may withdraw consent for such collection, use and disclosure, and make an access or correction request in respect of your personal data, in accordance with the Policy by emailing people@aspireapp.com.