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For Companies At a Glance
- Tasks: Use advanced data techniques to uncover trends and enhance customer value.
- Company: Join NewDay, a leader in the credit industry focused on innovation and customer satisfaction.
- Benefits: Enjoy flexible working options, professional development opportunities, and a supportive team culture.
- Why this job: Be part of a dynamic team that values creativity and drives impactful change through data.
- Qualifications: BSc in a data science field; proficiency in Python, SQL, and data visualisation required.
- Other info: Ideal for self-motivated individuals eager to learn and grow in a fast-paced environment.
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 external 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 perform 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: New Day
Contact Detail:
New Day 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 gain insights and potentially get referrals that could boost your application.
✨Tip Number 3
Showcase your proficiency in Python and SQL through personal projects or contributions to open-source projects. Having tangible examples of your skills can set you apart from other candidates.
✨Tip Number 4
Prepare to discuss your experience with model deployment and collaboration with DevOps teams. Being able to articulate your understanding of the entire model lifecycle will demonstrate your comprehensive knowledge and readiness 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 your relevant experience in data science, particularly your proficiency with Python and statistical modelling techniques. Include specific projects or roles where you've used these skills.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data science and how it aligns with the role at NewDay. Mention your experience with data wrangling and visualisation, and how you can contribute to their goals.
Showcase Your Skills: If possible, include links to any relevant projects or portfolios that demonstrate your data science capabilities, especially those involving machine learning and data manipulation. This will give them a clear picture of your expertise.
Prepare for Technical Questions: Be ready to discuss your technical skills in detail during the interview process. Brush up on your knowledge of SQL, Python libraries, and statistical techniques, as well as your experience with model deployment and data governance.
How to prepare for a job interview at New Day
✨Showcase Your Technical Skills
Be prepared to discuss your proficiency in Python and SQL. Bring examples of past projects where you used statistical modelling techniques or machine learning packages like scikit-learn, pandas, or numpy. This will demonstrate your hands-on experience and technical expertise.
✨Understand the Company and Industry
Research NewDay and the credit industry thoroughly. Familiarise yourself with their data resources and any recent trends in credit behaviours. This knowledge will help you tailor your responses and show your genuine interest in the role.
✨Prepare for Problem-Solving Questions
Expect questions that assess your analytical and problem-solving skills. Practice explaining your thought process when tackling data-related challenges, and be ready to discuss how you would approach model governance and lifecycle management.
✨Communicate Clearly and Effectively
Since the role requires strong communication skills, practice presenting complex findings in a clear and concise manner. Tailor your explanations to suit different audiences, showcasing your ability to adapt your communication style as needed.
