At a Glance
- Tasks: Analyse data and develop models to drive insights in fintech and payments.
- Company: Join a forward-thinking company in the heart of Northampton.
- Benefits: Flexible working days, competitive pay, and opportunities for growth.
- Other info: Collaborative team environment with a focus on innovation.
- Why this job: Make an impact in the fintech space while honing your data science skills.
- Qualifications: Experience with Python, R, SQL, and cloud platforms is essential.
The predicted salary is between 36000 - 60000 £ per year.
Our client is looking for a Data Scientist to join their team on a 12 month initial contract, working 2 to 3 days a week onsite in Northampton. This role would be working under an umbrella company.
Required Skills & Experience:
- Proven experience as a Data Scientist in payments, fintech, or enterprise analytics environments.
- Strong proficiency in Python, R, SQL, and data science libraries (e.g., scikit-learn, pandas, TensorFlow).
- Experience with cloud platforms (AWS, Azure, GCP) and big data tools (e.g., Spark, Databricks).
- Solid understanding of statistical modelling, machine learning, and data visualisation techniques.
- Excellent problem-solving, communication, and stakeholder engagement skills.
Data Scientist employer: LA International
Join a forward-thinking company that values innovation and collaboration, offering a dynamic work culture in Northampton. As a Data Scientist, you'll benefit from flexible working arrangements, professional development opportunities, and the chance to work with cutting-edge technologies in the fintech space. This role not only promises meaningful contributions to exciting projects but also fosters an environment where your skills can flourish and grow.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Network like a pro! Reach out to your connections in the fintech and data science space. Attend meetups or webinars, and don’t be shy about asking for introductions. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, R, or SQL. Use platforms like GitHub to share your code and visualisations. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and problem-solving abilities. Practice common data science interview questions and case studies. Remember, it’s not just about what you know, but how you communicate your thought process.
✨Tip Number 4
Apply through our website! We’ve got loads of opportunities that match your skills. Tailor your application to highlight your experience in payments and cloud platforms, and let us help you land that Data Scientist role!
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience in payments, fintech, or enterprise analytics. We want to see how your skills in Python, R, and SQL shine through, so don’t hold back!
Showcase Your Projects:Include specific projects where you've used data science libraries like scikit-learn or TensorFlow. We love seeing real-world applications of your skills, especially if they relate to cloud platforms or big data tools.
Craft a Compelling Cover Letter:Your cover letter is your chance to tell us why you’re the perfect fit for this role. Highlight your problem-solving abilities and communication skills, and don’t forget to mention your experience with stakeholder engagement!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the easiest way for us to keep track of your application and ensures you don’t miss out on any important updates!
How to prepare for a job interview at LA International
✨Know Your Tech Stack
Make sure you brush up on your Python, R, SQL, and the data science libraries mentioned in the job description. Be ready to discuss specific projects where you've used these tools, as well as any challenges you faced and how you overcame them.
✨Showcase Your Cloud Experience
Since the role involves cloud platforms like AWS, Azure, or GCP, prepare examples of how you've utilised these in past projects. Highlight any big data tools you've worked with, such as Spark or Databricks, and be ready to explain their impact on your work.
✨Demonstrate Your Problem-Solving Skills
Prepare to discuss real-world problems you've solved using statistical modelling or machine learning techniques. Use the STAR method (Situation, Task, Action, Result) to structure your answers and make them impactful.
✨Engage with Stakeholders
Communication is key! Think of examples where you've effectively engaged with stakeholders. Be ready to discuss how you translated complex data insights into actionable recommendations that non-technical team members could understand.
