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Responsibilities
* Use sophisticated statistical and machine learning techniques to identify new trends and relationships in data.
* Harvest, wrangle, and prototype new data sources internally and externally to create new value for NewDay and our customers.
* Provide quality and detailed data science outputs, sharing and following up with appropriate detail as requested by senior managers.
* Develop knowledge of all relevant data resources within NewDay and in the wider Credit Industry.
* Support the models throughout their lifecycle from conception, development, implementation, testing, and monitoring, with proper documentation to follow internal standards.
Essential Skills and Experience
* University degree in a highly analytical discipline (e.g., data science, mathematics, quantitative finance, economics).
* Proficiency in statistical data modeling techniques in Python.
* Experience working with raw datasets and performing data wrangling pre-modeling.
* Hands-on experience as a data scientist or modeller.
* Experience with credit risk, collections risk, affordability, IFRS9, or customer credit behavior models.
* Ability to present findings clearly, adapting the level of detail to the audience.
* Self-motivated and comfortable working in a fast-paced environment with evolving priorities.
* Strong sense of accountability, ownership, and excellent organizational and time management skills.
* Excellent interpersonal and written communication skills.
* Great team spirit, supporting colleagues on various tasks.
Desirable Skills and Experience
* MSc or PhD in a related field (e.g., Machine Learning, Statistics, Mathematics).
* Experience within a regulated financial services organization.
* Experience supporting model deployment and working with DevOps/Implementation teams.
Additional Information
We work with Textio to promote inclusive hiring practices.
Job Details
* Seniority level: Entry level
* Employment type: Full-time
* Job function: Engineering and Information Technology
Location: London, England, United Kingdom
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