Data Science Intern
Data Science Intern
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Job Description
Role/Programme:
As a Data Science Intern youll join our Data Science team in the summer. This is an exciting opportunity to kick start your career and make a meaningful impact. You will be joining us for 10 weeks (23rd June 29th August 2025).Youll be onboarded with the global internship cohort in one of our offices and learn the basics of being a Wiser.
How Youll Make an Impact: In this role you will:
- Youll work on a real data science project that matters to us using uptodate machine learning techniques. We cant say what project yet but your internship will be centred around this.
You will work directly on projects that impact our customers and will help us prioritise the most significant improvements to our products with their convenience and trust in mind.
Participate in building industryproven machine learning based solutions and find opportunities to experiment with stateoftheart algorithms.
Growth and Development:
At Wise we believe in continuous learning and development. You will have access to:
- Mentorship/ buddy programme: Weve a Buddy Programme for you to give you as much possible connection with people who know what youre going through.
- Weekly Lunch and learn sessions: These will be short intro presentations from various representatives of different business areas of Wise to make sure you have a chance to get to know as many teams and functions at Wise as possible
Qualifications :
- You are graduating in 2026 from a Bachelors or Masters degree potentially in Computer Science or any other STEM subject. However a degree in a technical field is not a must as our selection process prioritises your skills.
- You are able to start a 10 weeks internship from June 23rd
Knowledge of computer science and machine learning fundamentals including data structures algorithms data analysis linear algebra and statistics
You should have a good command of Python 3 and SQL and be familiar with major data analysis and ML frameworks
A selfstarted side project(s) that you are proud to talk about
Great communication skills and the ability to articulate complex technical concepts to a nontechnical audience
Eligible to work in London
And these would be great but arent essential:
Experience in applying machine learning methods to realworld problems
Familiarity with Bayesian methods in machine learning
Familiarity with challenges of supervised ML on imbalanced data
Familiarity with Apache Spark or other distributed processing frameworks
Experience in applying causal inference and/or uplift modelling techniques
Experience in software development from a previous internship
...Dont worry we dont expect you to know everything!
Additional Information :
Why Youll Love Working Here
You will have flexibility in how and where you work. We understand everyone needs a little something different so well do our best to make it happen but we recommend coming to the office as much as possible in your first weeks!
Weekly office lunch and breakfast coffee tea and snacks!
Gross Yearly Salary (prorated) 42000 GBP
Fun and creative offices with social activities
Be part of a global team with a global mindset.
Have a real impact. Solve real customer problems.
For more details on locationspecific benefits please check here.
If you are excited about this opportunity and youre confident in your abilities but dont hit every mark on our list we still want to hear from you! Dont hesitate to apply by submitting your updated resume!
For everyone everywhere. Were people building money without borders without judgement or prejudice too. We believe teams are strongest when they are diverse equitable and inclusive.
Were proud to have a truly international team and we celebrate our differences.
Inclusive teams help us live our values and make sure every Wiser feels respected empowered to contribute towards our mission and able to progress in their careers.
If you want to find out more about what its like to work at Wise visit Wise.Jobs.
Keep up to date with life at Wise by following us on LinkedIn and Instagram.
Remote Work :
No
Employment Type :
Fulltime
Employment Type
Full-time
