Hybrid opportunity at
WiseLead Data Scientist - Receive Risk
Wise is seeking a Lead Data Scientist to join the Receive Team based in London on a hybrid work arrangement. This position involves designing and launching…
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About This Role
Wise is seeking a Lead Data Scientist to join the Receive Team based in London on a hybrid work arrangement. This position involves designing and launching machine learning models and data science solutions that govern how customers add and receive funds, balancing risk mitigation with a smooth user experience. The selected candidate will examine extensive datasets, build scalable modelling approaches, run experiments, and work closely with product, engineering, analytics, operations,…
Job Description
Wise is seeking a Lead Data Scientist to join the Receive Team based in London on a hybrid work arrangement. This position involves designing and launching machine learning models and data science solutions that govern how customers add and receive funds, balancing risk mitigation with a smooth user experience. The selected candidate will examine extensive datasets, build scalable modelling approaches, run experiments, and work closely with product, engineering, analytics, operations, and risk management departments. This role suits an experienced data professional who can independently drive data initiatives, collaborate across technical and non-technical teams, and help shape financial transaction systems that serve millions of global customers.
Responsibilities
- Lead the creation and implementation of machine learning models and data science solutions to enhance Receive product performance across multiple markets
- Examine large amounts of transaction, customer, and product data to uncover patterns, trends, risks, and new opportunities
- Design and execute experiments to measure the impact of product modifications, decision systems, and customer experience enhancements
- Construct scalable modelling frameworks to assist with prioritization, personalization, risk management, and operational choices
- Partner with analysts, engineers, product managers, operations, and risk groups to turn business needs into practical data science solutions
- Build reliable data pipelines, algorithms, and tools to power production-ready modelling and decision-making
- Keep up-to-date with modern developments in data science, machine learning, and payment fraud prevention methods
Requirements
- Proven background in deploying models from scratch, encompassing data preprocessing, feature engineering, model selection, evaluation, and monitoring
- Strong proficiency in Python with the ability to write, justify, and review code, alongside knowledge of Git for collaboration through GitHub pull requests
- Capability to read and understand code written in Java
- Demonstrated experience working alongside engineering teams on services
- Background handling large datasets and data processing technologies such as SQL, Hadoop, and Spark
- Familiarity with supervised learning, unsupervised learning, anomaly detection, and real-time data analysis
- Statistical analysis expertise combined with presentation skills to communicate insights effectively to both technical and non-technical audiences
- Independent problem-solving abilities within a cross-functional and cross-team environment
Qualifications
- Experience utilizing MLOps tools such as MLflow, Airflow, AWS SageMaker, AWS S3, AWS EMR, and CI/CD
- Prior background in the fraud domain with a solid understanding of fraud detection methods
- Experience designing and deploying LLM-based solutions in production environments
Core Skills
Benefits
- Stock options in a profitable company
- Hybrid working model providing flexibility for remote work, overseas work, and personal commitments
- Annual personal development budget for books, courses, or conferences
- Visa and relocation support
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
Where is this job located?
This role is based in London and uses a hybrid working model.
What is the employment type?
The job posting states that the position is full-time.
What benefits does Wise offer for this role?
Benefits include stock options in a profitable company, a hybrid working model, an annual personal development budget, and visa and relocation support.
Is a specific formal qualification required?
The posting states that formal qualifications are not strictly important, provided you have great experience and can articulate your thinking.
What is the salary for this position?
The salary is not stated in the job posting.
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