Applied Scientist, Fintech (Fraud)

Job Description

Our Applied Scientists at Wolt build and deploy applied science and machine learning solutions to address a wide variety of challenging business problems.

Utilizing a spectrum of methodologies including statistical analysis, machine learning, deep learning and operations research, they improve critical processes within Wolt's online delivery platform and business operations.

Their contributions significantly impact all 28 countries in which we operate.

The work consists of owning applied science use cases as part of a product development team; starting from identifying opportunities, to developing and prototyping a solution, all the way to deploying, maintaining, and improving it in production.

We use a variety of technologies and tools including Python, SQL, Snowflake, Flyte, MLflow and Seldon Core to get the job done, and are constantly looking for ways to improve how our applied scientists work.

We are looking for an Applied Scientist to be embedded into our cross-functional Payments Tooling team in Fintech , to work together with software engineers, and product, design and analytics people, to develop algorithms and solutions for fraud prevention.

Initially, the work focuses on payment fraud but potentially expands to other kinds of fraud seen on the Wolt platform. There are opportunities to work on machine learning models such as risk scoring and identity resolution.

This is the first embedded applied scientist role in that team, so here’s an opportunity to start something new and set the direction together with the team, besides shaping the future of fraud prevention across Wolt products.

This role can be based in one of our tech hubs in Helsinki, Berlin, or Stockholm.

Qualifications

You have plenty of hands-on experience with production-level Applied Science and Machine Learning projects from prototyping to deploying, maintaining and improving production deployed solutions (i.

• e. ability and interest to handle a use case end-to-end);
• You have a deep understanding and experience with machine learning and a solid understanding of statistics. You understand what it takes to train models for rare events, and build inference services for a real-time environment;

Proven ability to tackle highly complex domains, break them down into solvable problems and develop novel solutions to them.

• You can fluently discuss technical concepts and matters with non-technical stakeholders;
• You have previous experience in Fintech domain;
• Knowledge of experimental design and analysis, such as A / B testing;

You have solid engineering skills and code fluently in Python, which is our main language for applied science projects, and experience with databases (SQL).

• You value good software engineering practices, understand MLOps, and take pride in the quality of your code and the performance of your solutions;
• Ideally, you’ll also have a degree in a field relevant to Applied Science;
• You’re an analytical, curious and proactive problem solver. We’re looking for a self-starter with a drive to get things done.

Also as well a good communicator, willing to collaborate with people inside and outside of the team.

Additional Information

The position will be filled as soon as we find the right person, so make sure to apply as soon as you realize you really, really want to join us!

The compensation will be a negotiable combination of monthly pay and DoorDash RSUs. The latter makes it exceptionally easy to be excited about our company growing and doing well, as you’ll own a piece of the pie.

For any further questions about the position, you can turn to Product+ Talent Acquisition Partner - Fernanda ([email protected]).