Job Description Who we are This ad goes out to all those who want to find a purpose in what they’re doing and take accountability for their work. At Blinkist, we’ve created a meaningful product that is growing fast. Our blinks – key insights from the world’s best nonfiction – help more than 10 million people around the globe to keep learning new, exciting things each and every day. In 2017, we received the United Nations World Summit Award in the Learning & Education category, a Google Material Design Award for Brand Expressiveness, as well as an Android Excellence Award. Why we need you Our data stack has always been a core pillar of our business success. We’ve spent the past years developing solutions to gather key data points that can fuel complex algorithms and predictive models, and through them create value for our users. In order to continue delivering on this vision, we are looking for an experienced Data Scientist to join our small but well-equipped team. The ideal candidate should have experience in setting up and managing recommender models, be enthusiastic about NLP and using the power of data to remove uncertainties innate to subscription models (i.e. churn predictions). You will not only take part in a wide spectrum of projects and work closely with business stakeholders but also improve the customer experience immensely through personalization. Responsibilities – Design and implement an array of recommender systems to provide our users with the right content at the right time; – Perform analyses of structured and unstructured data; take part in data science projects ranging from data exploration to model building, performance evaluation, and testing; – Utilize advanced statistical techniques to predict churn likelihood, attribute signup/purchase to the right channels and reduce uncertainties that come with the subscription business; – Crunch vast amounts of data in order to understand user behavior, extract valuable insights, identify new product opportunities and model improvements; – Apply Natural Language Processing techniques to categorize our content better; – Develop high-performance algorithms in scalable and product-ready code, and collaborate with our Data Engineering team to develop new data structures and to put algorithms in production. Requirements – You have 4+ years experience in applied data science; – Your expertise lies in building end to end data science solutions; – You've worked with the Python ecosystem: Pandas, NumPy, Scikit-learn, Jupyter – You are fluent in PostgreSQL – You have good knowledge of software architecture and design patterns – You are skilled data-visualiser and you can communicate data-analytic insights effectively – You have experience with the AWS landscape, ideally played around with SageMaker – [Bonus] Practical experience with prediction.io – [Bonus] Experience with RESTful APIs (implementation and consumption) – [Bonus] Previous work experience in a subscription business – [Bonus] Knowledge of information retrieval techniques – [Bonus] Contributions to open source What’s in it for you At Blinkist, we got rid of classical management hierarchies and, instead, distributed authority among all colleagues. We created our own Blinkist Operating System and foster a unique company culture championing self-empowerment, personal development, direct communication, and mutual support. We offer a fantastic workplace in the heart of Berlin-Neukölln with perks like a yearly personal development budget of 1,600€, free lunch, a gym membership, a public transportation pass, language classes and 30 days of vacation. If we’ve captured your interest and you want to take part in building the leading destination for the modern lifelong learner, apply now and let us know why you’re the perfect fit for the job! At Blinkist, we don’t just accept difference — we celebrate it and support it. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, or gender identity.