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For Companies At a Glance
- Tasks: Use advanced data techniques to uncover trends and optimise customer journeys.
- Company: Join NewDay, a leader in the credit industry focused on innovation and customer value.
- Benefits: Enjoy flexible working options, a supportive team environment, and opportunities for personal growth.
- Why this job: Make a real impact with your data skills while collaborating in a dynamic, fast-paced culture.
- Qualifications: BSc in Data Science or related field; proficiency in Python and SQL required.
- Other info: Ideal for self-motivated individuals eager to learn and grow within a collaborative team.
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 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.
- 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- Data Scientist - Journey Optimisation employer: New Day
Contact Detail:
New Day Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist- Data Scientist - Journey Optimisation
✨Tip Number 1
Familiarise yourself with the latest trends in data science, particularly in machine learning and statistical modelling. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Showcase your proficiency in Python and SQL by working on personal projects or contributing to open-source initiatives. Having tangible examples of your skills can set you apart from other candidates.
✨Tip Number 3
Network with professionals in the financial services sector, especially those who work in data science roles. Attend industry meetups or webinars to gain insights and potentially get referrals for the position.
✨Tip Number 4
Prepare to discuss how you've handled data wrangling and model deployment in past experiences. Being able to articulate your problem-solving process will demonstrate your analytical skills and fit for the role.
We think you need these skills to ace Data Scientist- Data Scientist - Journey Optimisation
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 achievements that demonstrate your skills in data wrangling and visualisation.
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 understanding of the financial services industry and how your skills can contribute to their goals, especially in journey optimisation.
Showcase Your Technical Skills: Provide examples of your experience with tools like scikit-learn, pandas, and SQL. If possible, include links to any relevant projects or portfolios that showcase your ability to analyse data and derive insights.
Demonstrate Soft Skills: Highlight your interpersonal and communication skills in your application. Mention experiences where you successfully collaborated with teams or presented complex findings to non-technical audiences, as these are crucial for the role.
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.
✨Prepare for Data Wrangling Questions
Expect questions about your experience with raw datasets and data wrangling. Be ready to explain your approach to cleaning and managing data, as well as any challenges you've faced and how you overcame them. This shows your problem-solving skills and analytical mindset.
✨Communicate Clearly
Since the role involves sharing detailed data science outputs, practice explaining complex concepts in simple terms. Tailor your explanations to different audiences, showcasing your ability to adapt your communication style based on who you're speaking to.
✨Demonstrate Your Passion for Data
Express your enthusiasm for data science and modelling techniques during the interview. Share examples of how you've driven value from data in previous roles or projects. This will highlight your motivation and alignment with the company's goals.
