Senior Data Scientist (Recommendation Systems Expert) (f/m/d)

adjoe is a leading mobile ad platform developing cutting-edge advertising and monetization solutions that take its app partners’ business to the next level. Part of the applike group ecosystem, adjoe is home to an advanced tech stack, powerful financial backing from Bertelsmann, and a highly motivated workforce to be reckoned with.

Meet Your Team: WAVE Data Science

Did you know that in-app ads are sold in a real-time auction before they get rendered in thousands of mobile apps? Dozens of ad networks compete for every single view, choosing their best ad and deciding what price to bid in just a couple hundred milliseconds. We at adjoe have developed our own ad network that takes part in this competition, fighting against giants like Google, Meta and TikTok to present its own ads. To stand a chance in this fierce competition, the WAVE Data Science team builds creative algorithms using technologies ranging from simple linear regression to advanced deep learning models. Everything we do is based on solid research about user behavior as well as publisher and advertiser analysis to build competitive bidding algorithms that balance the advertisers’ goals, the publishers’ expectations and of course the user experience. To make our inventions come to life we use state-of-the art technology and work closely with the product and business teams to shape the future of adjoe’s core business and technologies.

What You Will Do

• Dive into state-of-the-art algorithms and deep learning models to create recommendation systems, predict user behavior, and optimise user retention.
• Conduct research and hypothesis testing to come up with ideas that can improve our bidding algorithm.
• Drill into data from various sources to generate insights and discuss them with your colleagues.
• Transform recurring analyses into KPIs and Dashboard Views we can easily monitor.
• Act as an advocate for data-related topics in the company and become the go to person in your area of expertise.

Who You Are

• You have 4+ years of professional experience in the Data Science field working in adtech, e-commerce, social media or a similar industry.
• You have shown a great level of understanding of deep neural networks (libraries such as tensorflow and pytorch) and have experiences developing deep neural networks for recommendation systems.
• You have a strong knowledge of Python, R, Scala, Julia or similar typical programming languages for Data Science.
• You have experience drilling into large amounts of data coming from various sources – including AWS Athena, Kafka, Spark, Flink, S3, MySQL.
• You are able to dive deep into mathematical foundations and explain complex topics in a simple way.
• You are a strong team player and enjoy helping others.
• Plus: Experiences in deep cross networks and multi-task deep learning.

Heard of Our Perks?

• Work-Life Package: 2 remote days per week, 30 vacation days, 3 weeks per year of remote work, flexible working hours, dog-friendly kick-ass office in the center of the city.
• Relocation Package: Visa & legal support, relocation bonus, reimbursement of German Classes costs, and more.
• Happy Belly Package: Monthly company lunch, tons of free snacks and drinks, free breakfast & fresh delicious pastries every Monday
• Physical & Mental Health Package: In-house gym with a personal trainer, various classes like Yoga with expert teachers & free of charge access to our EAP (Employee Assistance Program) to support your mental health and well-being
• Activity Package: Regular team and company events, and hackathons.
• Education Package: Opportunities to boost your professional development with courses and training directly connected to your career goals 
• Wealth building: virtual stock options for all our regular employees

Skip writing cover letters. Tell us about your most passionate personal project, your desired salary and your earliest possible start date. We are looking forward to your application!

We welcome applications from people who will contribute to the diversity of our company.