Data Scientist

Our mission

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 six countries and are 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, with over 7 million users. And, we’re still in the early days of our product roadmap and potential impact on people’s everyday lives.

We’re looking for an experienced Data Scientist and 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.
• We’re hiring for multiple Senior Data Analyst roles across different functions (Finance, Customer Support). Your final scope and responsibilities will be aligned to the team you join, and clearly outlined in your offer.

Requirements

• Education and Experience
• 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 you 

• 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.

#LI-REMOTE

Our team

• We have a rapidly growing in-country team in Senegal, Côte d'Ivoire, Mali, Burkina Faso, The Gambia, and Uganda, 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.