Hybrid opportunity at
WiseLead Data Scientist - Recieve Risk
Wise is seeking a Lead Data Scientist to join the Receive Team based in London. This hybrid position focuses on understanding financial transactions to mitigate risk…
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About This Role
Wise is seeking a Lead Data Scientist to join the Receive Team based in London. This hybrid position focuses on understanding financial transactions to mitigate risk while delivering smooth customer experiences. The professional chosen for this role will design, build, and deploy machine learning models that impact millions of users and influence global product performance across different markets. Working within a multidisciplinary environment, the individual will collaborate closely with engineering,…
Job Description
Wise is seeking a Lead Data Scientist to join the Receive Team based in London. This hybrid position focuses on understanding financial transactions to mitigate risk while delivering smooth customer experiences. The professional chosen for this role will design, build, and deploy machine learning models that impact millions of users and influence global product performance across different markets. Working within a multidisciplinary environment, the individual will collaborate closely with engineering, product management, analytics, operations, and risk professionals.
This opportunity suits an experienced practitioner who can build models from scratch, handle large volumes of data, and translate complex business problems into actionable technical solutions. Candidates should possess strong programming abilities, particularly in Python, along with the capacity to coordinate effectively with cross-functional teams and communicate technical findings to non-technical audiences.
Wise operates on a hybrid schedule, providing flexibility for home working, overseas locations, and personal schedules. The company offers financial incentives, relocation support, and a dedicated personal development budget for career growth. Qualified individuals who thrive independently and want to contribute to an international environment are encouraged to apply.
Responsibilities
- Lead the creation and implementation of machine learning models and data solutions to enhance the Receive product across various markets
- Examine large sets of customer, product, and transaction data to spot trends, hazards, and patterns
- Run experiments to gauge the success of product updates, decision-making frameworks, and user experience enhancements
- Construct scalable modeling strategies that assist with prioritization, personalization, risk mitigation, and operational choices
- Partner with analysts, engineers, product managers, operations, and risk groups to turn business needs into working data science outputs
- Build reliable data pipelines, algorithms, and utilities to back production-grade models
- Keep up-to-date with modern data science, machine learning, and payment fraud prevention methods
Requirements
- Proven track record of building and deploying models from scratch, spanning preprocessing, feature engineering, selection, evaluation, and monitoring
- Solid proficiency in Python with the ability to write, justify, and review code
- Knowledge of Git for collaboration, such as opening Pull Requests on GitHub
- Ability to read through Java code
- Demonstrable experience partnering with engineering teams on services
- Experience handling large datasets and processing technologies like Hadoop, Spark, or SQL
- Familiarity with anomaly detection, supervised learning, unsupervised learning, and real-time data analysis
- Statistical analysis skills coupled with good presentation abilities to turn insights into action
- Strong product mindset paired with the capability to operate independently in cross-functional settings
- Good communication skills with the ability to explain concepts to non-technical stakeholders
- Strong problem-solving abilities to refine problem statements and determine solutions
Qualifications
- Experience utilizing MLOps tools such as Airflow, MLflow, AWS SageMaker, AWS S3, AWS EMR, and CI/CD pipelines
- Prior background in the fraud sector paired with a solid grasp of fraud detection methodologies
- Experience in designing and deploying Large Language Model-based solutions within production environments
Core Skills
Benefits
- Stock options in a profitable company
- Hybrid working model with schedule flexibility
- 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 position is based in London.
What is the remote work policy?
The role utilizes a hybrid working model that offers flexibility for working from home, working overseas, or handling personal commitments.
What is the salary for this role?
The job posting does not specify the salary.
What employment type is this?
This is a full-time position.
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