Data Scientist in London

Data Scientist in London

London Full-Time 36000 - 60000 ÂŁ / year (est.) No home office possible
Wave Mobile Money

At a Glance

  • Tasks: Join us to analyse data and drive impactful financial solutions for millions in Africa.
  • Company: Wave, a leading fintech revolutionising financial services across Africa.
  • Benefits: Competitive salary, remote work, generous leave, and annual travel stipend.
  • Why this job: Make a real difference by optimising financial services for underserved communities.
  • Qualifications: Bachelor's degree in a quantitative field and 4+ years of data science experience.
  • Other info: Work with a passionate team dedicated to financial inclusion and innovation.

The predicted salary is between 36000 - 60000 ÂŁ per year.

Get AI-powered advice on this job and more exclusive features. We're making Africa the first cashless continent. In 2017, over half the population in Sub-Saharan Africa had no bank account. That’s for good reason—the fees are too high, the closest branch can be miles away, and nobody takes cards. Without access to financial institutions, people are forced to keep their savings under the mattress. Small business owners rely on lenders who charge extortionate rates. Parents spend hours waiting in line to pay school fees in cash.

We’re solving this by building financial services that just work: no account fees, instantly available, and accepted everywhere. In places where electricity, water and roads don’t always work, you can still send money with Wave. In 2017, we launched a mobile app in Senegal for cash deposit, withdrawal, and peer-to-peer and business payments. Now, we have millions of users across 9 countries and we’re growing fast.

Our goal is to make Africa the first cashless continent and that’s where you come in...

How you’ll help us achieve it:

  • Wave is now the largest financial institution in Senegal and CĂ´te d’Ivoire, with millions of users, growing rapidly year-on-year.
  • We’re looking for an experienced Data Scientist to help grow and strengthen our user base.
  • You’ll work on high-impact use cases with millions of users, such as optimizing our existing scratch card rewards program or designing and launching entirely new initiatives from scratch.
  • The technical challenges range from crafting simple heuristics when data is sparse to applying advanced techniques like geospatial analytics, network analysis, and uplift modeling.
  • You’ll own the full cycle: defining the right approach, implementing it, and shipping it in production.
  • This role is highly experimentation-driven: you’ll be able to rapidly test ideas, learn from real user feedback, and iterate quickly.

We’re looking for someone who is product-minded, hands-on, and pragmatic: a data scientist who sees beyond models and algorithms and thinks deeply about how data connects to intuitive user behavior and real-world impact.

In this role you’ll:

  • Be part of a multidisciplinary team, working with engineers, data analysts, economists and a product manager.
  • Focus on advanced analytics and machine learning problems, delivering them end-to-end independently.
  • Prioritise work and shape your own approach in a way that maximises the positive impact on both users and the business.
  • Engage not just with business metrics, but also collaborate closely with Operations teams to understand the real-world outcomes and impact of your work.

Key Details:

  • You can work remotely from anywhere (between UTC -5 and +2) with reliable Internet access.
  • Wave covers travel once per year to one of our operating countries in Africa, as well as a yearly stipend of $1,200 to meet with coworkers.
  • Our salaries are competitive and are calculated using a transparent formula. For this role, depending on your level and location, we offer a salary of up to $149,200 USD (paid in your local currency equivalent), plus a generous equity package.

Major benefits:

  • Subsidized health insurance for you and your dependents and retirement contributions (both vary from country to country).
  • 6 months of fully paid parental leave and subsidized fertility assistance.
  • Flexible vacation, with most folks taking between 21-30 days exclusive of statutory holidays.
  • $10,000 annual charitable donation matching.

Requirements:

  • Minimum Bachelor’s degree in a quantitative field such as Statistics, Mathematics, Economics, Computer Science, Engineering, or a related discipline. A Master’s or PhD is a plus.
  • 4+ years experience in applied data science or similar experience.
  • Demonstrated experience with data analysis, machine learning and product A/B tests.
  • Experience in using advanced analytics for optimising targeting, rewards or incentive programs is a big plus.

Technical skills:

  • Proficiency in applying machine learning methods to solve business problems.
  • Very strong Python skills with expertise in data manipulation, analysis and machine learning. Must be comfortable writing code that runs in production.
  • Competent in SQL.
  • Solid foundation in probability and statistics.

You might be a good fit if:

  • Thrive on spotting key problems and finding the fastest, most effective solutions.
  • Enjoy and excel at working on machine learning and statistics problems.
  • Quickly build and validate proof-of-concept solutions, refining based on real-world feedback.
  • Prefer pragmatic approaches but apply complex methods when the impact is worth it.
  • Work iteratively, knowing when a project is "good enough" to avoid over-polishing.
  • Communicate insights clearly to all audiences and make confident, data-driven recommendations.

Our team:

  • We have a rapidly growing in-country team in Senegal, CĂ´te d’Ivoire, Mali, Burkina Faso, The Gambia, Uganda, Niger, Sierra Leone, and Cameroon plus remote team members spread across the world.
  • We’re deeply passionate about our mission of bringing radically affordable financial services to the people who need them most.
  • We foster autonomy for our employees. You’ll own your projects at every stage, from understanding the problem to monitoring your solution in production.
  • We raised the largest Series A in Africa in 2021. Our world-class investors include Founders Fund, Sequoia Heritage, Stripe, Ribbit Capital, Y Combinator, and Partech Africa.
  • We are on Y Combinator's top companies by revenue.

How to apply:

Fill out the form below, and upload a resume in English and a cover letter describing your interest in Wave and the role. We review applications frequently and recommend that you apply to the role that most closely aligns with your skills, experience and career goals. Wave is an equal‐opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Data Scientist in London employer: Wave Mobile Money

Wave is an exceptional employer dedicated to transforming financial services in Africa, offering a dynamic work culture that prioritises innovation and collaboration. Employees enjoy competitive salaries, generous benefits including subsidised health insurance and flexible vacation, as well as unique opportunities for professional growth through hands-on projects that directly impact millions of users. With the flexibility to work remotely and the chance to travel within Africa, Wave fosters an environment where passionate individuals can thrive while making a meaningful difference.
Wave Mobile Money

Contact Detail:

Wave Mobile Money Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Data Scientist in London

✨Tip Number 1

Network like a pro! Reach out to people in the industry, attend meetups, and connect with current employees at Wave. A friendly chat can sometimes lead to job opportunities that aren't even advertised.

✨Tip Number 2

Show off your skills! Create a portfolio showcasing your data science projects, especially those that relate to financial services or user behaviour. This will give you an edge and demonstrate your hands-on experience.

✨Tip Number 3

Prepare for interviews by practising common data science questions and case studies. Think about how your past experiences can translate into solving real-world problems at Wave. Confidence is key!

✨Tip Number 4

Don't forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in being part of our mission to make Africa cashless.

We think you need these skills to ace Data Scientist in London

Data Analysis
Machine Learning
Python
SQL
Probability and Statistics
A/B Testing
Geospatial Analytics
Network Analysis
Uplift Modelling
Problem-Solving Skills
Communication Skills
Experimentation
Product Mindset
Collaboration

Some tips for your application 🫡

Tailor Your Resume: Make sure your resume speaks directly to the Data Scientist role. Highlight relevant experience, especially in data analysis and machine learning, and don’t forget to showcase any projects that align with our mission at Wave.

Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share why you’re passionate about making Africa cashless and how your skills can help us achieve that. Be genuine and let your personality come through!

Showcase Your Technical Skills: We want to see your technical prowess! Include specific examples of how you've used Python, SQL, and machine learning methods in past projects. This will help us understand your hands-on experience and problem-solving abilities.

Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy—just fill out the form and upload your documents!

How to prepare for a job interview at Wave Mobile Money

✨Know Your Data Science Stuff

Make sure you brush up on your data science fundamentals, especially in machine learning and statistics. Be ready to discuss your past projects and how you've applied these techniques to solve real-world problems, as this role is all about making an impact with data.

✨Understand the Company’s Mission

Wave is all about making Africa the first cashless continent. Familiarise yourself with their products and the challenges they face. Show that you’re not just a data scientist but someone who genuinely cares about their mission and can contribute to it meaningfully.

✨Prepare for Practical Scenarios

Expect to tackle practical problems during the interview. Think about how you would approach optimising a rewards program or designing a new initiative. Be ready to explain your thought process and how you would iterate based on user feedback.

✨Communicate Clearly

You’ll need to convey complex insights to various audiences. Practice explaining your findings in simple terms, focusing on how your work impacts users and the business. This will demonstrate your ability to bridge the gap between data and real-world applications.

Data Scientist in London
Wave Mobile Money
Location: London

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