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For Companies At a Glance
- Tasks: Analyse data using advanced techniques to uncover trends and insights.
- Company: Join NewDay, a leader in innovative consumer credit solutions.
- Benefits: Enjoy a dynamic work environment with opportunities for growth and development.
- Why this job: Make a real impact by driving value from data in a fast-paced industry.
- Qualifications: BSc in Data Science or related field; proficiency in Python and SQL required.
- Other info: Work with a supportive team and embrace a culture of learning and collaboration.
The predicted salary is between 36000 - 60000 £ per year.
What will you be doing day-to-day?
- 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 NewDay to create new value for NewDay and our customers.
- Provide quality and detailed data science outputs, sharing and following up with as much detail as appropriate or requested by senior managers.
- Develop knowledge of all relevant data resources within NewDay and in the wider Credit Industry.
- Governance: support the models throughout their lifecycle from conception, development, implementation, testing and monitoring, with the required level of documentation to follow internal procedures and standards.
Your Skills and Experience
ESSENTIAL
- At least a BSc or higher university degree in a data science related field (e.g. machine learning, statistics, mathematics).
- Proficiency in statistical data modelling techniques.
- Proficiency with Python, including experience with statistics/machine learning packages such as scikit-learn, pandas, numpy, etc.
- Good SQL/data manipulation skills required including cleaning and managing data.
- Experience in data visualisation and communication.
- Experience with working with raw datasets and performing data wrangling pre-modelling.
- Analytical and problem-solving skills.
DESIRABLE
- MSc or PhD in Data Science related field (e.g. Machine Learning, Statistics, Mathematics).
- Experience within a regulated financial services organization.
- Ability to present sophisticated findings clearly, adapting the level of detail to the audience.
- Experience in supporting model deployment and working with DevOps/Implementation teams.
Your Personal Attributes
- Self-motivated, comfortable working in a fast-paced environment where priorities evolve.
- Honest and hardworking with a will to learn as well as develop others.
- Strong sense of accountability and ownership, with great organizational, planning and time management skills.
- Passionate about modelling and techniques to drive value from data.
- Personable with excellent interpersonal & written communication skills.
- Ability to build strong and effective working relationships with people across all levels of the organisation.
- Ability to embrace company culture and embed into day-to-day interactions.
- Great team spirit, supporting team and colleagues on tasks big and small.
Data Scientist - Credit Behaviours employer: NewDay Ltd
Contact Detail:
NewDay Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - Credit Behaviours
✨Tip Number 1
Familiarise yourself with the latest trends in data science, particularly in credit behaviours. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the financial services sector, especially those working in data science roles. Attend industry meetups or webinars to build connections and gain insights that could give you an edge in your application.
✨Tip Number 3
Brush up on your Python skills, focusing on libraries like scikit-learn and pandas. Consider working on personal projects or contributing to open-source projects to showcase your proficiency and practical experience.
✨Tip Number 4
Prepare to discuss your experience with data visualisation and communication. Think of examples where you've successfully presented complex data findings to non-technical audiences, as this is crucial for the role.
We think you need these skills to ace Data Scientist - Credit Behaviours
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience and skills that align with the Data Scientist role. Emphasise your proficiency in Python, SQL, and any statistical modelling techniques you've used.
Craft a Strong Cover Letter: Write a cover letter that showcases your passion for data science and your understanding of credit behaviours. Mention specific projects or experiences that demonstrate your analytical and problem-solving skills.
Showcase Your Technical Skills: In your application, provide examples of how you've used machine learning techniques and data visualisation tools in past roles. This will help illustrate your capability to handle the responsibilities outlined in the job description.
Prepare for Potential Questions: Think about how you would explain complex data findings to a non-technical audience. Be ready to discuss your approach to data wrangling and model deployment, as these are key aspects of the role.
How to prepare for a job interview at NewDay Ltd
✨Showcase Your Technical Skills
Be prepared to discuss your proficiency in Python and statistical modelling techniques. Bring examples of past projects where you've used libraries like scikit-learn or pandas, and be ready to explain your approach to data wrangling and visualisation.
✨Understand the Company and Industry
Research NewDay and the credit industry thoroughly. Familiarise yourself with their products and services, as well as current trends in credit behaviours. This will help you demonstrate your interest and how your skills can add value.
✨Prepare for Problem-Solving Questions
Expect to face analytical and problem-solving scenarios during the interview. Practice explaining your thought process clearly and concisely, showcasing how you approach complex data challenges and derive insights from raw datasets.
✨Demonstrate Strong Communication Skills
Since the role involves sharing detailed data science outputs, practice articulating your findings in a way that is accessible to non-technical stakeholders. Tailor your communication style to suit different audiences, highlighting your ability to build effective working relationships.