Opportunity at
WiseLead Data Scientist - Treasury Liquidity
Wise is seeking a Lead Data Scientist specializing in Treasury Liquidity to join its London office on a full-time, on-site basis. This role sits at the…
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About This Role
Wise is seeking a Lead Data Scientist specializing in Treasury Liquidity to join its London office on a full-time, on-site basis. This role sits at the intersection of data science and treasury operations, focusing on the design and implementation of forecasting models that manage liquidity and control financial risks. The successful candidate will collaborate with engineering, product, and operational groups to build data-driven solutions that optimize cash placement across multiple…
Job Description
Wise is seeking a Lead Data Scientist specializing in Treasury Liquidity to join its London office on a full-time, on-site basis. This role sits at the intersection of data science and treasury operations, focusing on the design and implementation of forecasting models that manage liquidity and control financial risks.
The successful candidate will collaborate with engineering, product, and operational groups to build data-driven solutions that optimize cash placement across multiple regions, currencies, and products. Responsibilities include formulating supply and demand projections, integrating models into operational back-office systems, and preparing for stress scenarios and new product deployments. The position also entails creating infrastructure to analyze liquidity usage, presenting risk assessments to senior stakeholders and the second line of defence, and translating complex risk concepts into clear, actionable strategies.
This opportunity is well-suited for an autonomous professional with a strong product mindset, solid coding proficiency in Python, and experience working alongside software engineers in cross-functional settings. Candidates should possess a strong foundation in statistics, machine learning, linear algebra, or optimization, paired with the communication skills needed to convey complex technical findings to non-technical audiences.
Responsibilities
- Design, implement, and refine forecasting models for liquidity management and risk control
- Partner with Treasury operations to create supply and demand projections integrated into real-time money movement across global products and currencies
- Conduct data analysis to support liquidity efficiency initiatives and balance sufficiency with excess
- Coordinate with engineering teams to deploy models within the treasury operational backoffice
- Build custom models and analyses for stress events and product launches
- Develop infrastructure to track liquidity consumption across company products
- Translate complex liquidity risk scenarios into actionable insights in cooperation with product and operational teams
- Document and present risk assessments and model outcomes to senior leadership, controllers, and the Risk team
Requirements
- Strong Python knowledge with the ability to read code
- Demonstrated experience collaborating with software engineers
- Familiarity with big data technologies such as Hadoop or Spark
- Experience using cloud platforms like AWS, GCP, or Azure, and data warehousing tools
- Strong knowledge in statistics, machine learning, linear algebra, or optimization
- Product mindset with the ability to operate autonomously in cross-functional environments
- Strong communication skills for interacting with non-technical individuals
- Problem-solving capabilities to refine problem statements and determine solutions
Qualifications
- Experience in supply and demand modeling and forecasting within supply chain optimization or financial company liquidity management
Core Skills
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
What is the location of this role?
This position is based on-site in London.
What is the employment type?
The role is full-time.
What salary does this position offer?
The source posting does not specify a salary.
What are the core technical skills required?
Candidates must have strong Python programming skills, the ability to read code, experience working with engineers, familiarity with big data tools like Hadoop or Spark, and knowledge of cloud platforms and data warehousing.
Sample Interview Questions
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