• 3+ years of experience modeling large, complex data sets
• Experience designing models and evaluating the trade-offs between accuracy, efficiency, complexity, interpretability, etc
• Appreciation for the unique challenges of networked data (in comparison to tabular, textual, or image data)
• Comprehensive understanding of the fundamentals of data science: classification, regression, clustering, dimensionality reduction, deep learning etc
• Advanced coding skills in Python, familiarity with Docker, AWS
• Ability and willingness to rapidly learn advanced topics in network science and machine learning
• Ability to prototype rapidly and also ship maintainable, production-ready code
• A growth mindset, being able to balance long term objectives with the immediate development needs of the company and translate them into data science initiatives
• You can communicate concepts at different levels of complexity i.e. you can change your explanation depending on the audience. You think of what information the person you are talking to needs and you frame it in the context useful to them
• You're highly collaborative with strong verbal and written communication skills
• You enjoy writing documentation and understand why it's valuable

Desirable

• In this role you will work on a small, but extremely dynamic and competent data science team
• This is one of those rare places where you will be pushed to your limits and learn a lot in short time
• As a data scientist, you will work with other data scientists to make the most accurate understanding of everyone's public digital footprint
• You will be discovering, defining, and working on problems that nobody has solved before with some of the smartest people
• You can find interesting problems and propose to work on them as long as they fit within the larger scope of research and business goals of the organization
• You will have freedom in choosing how to approach solving problems you are working on and which technologies to use. If you can show that it's the best way to solve the problem at hand, all tradeoffs considered, you can use it
• Envision, implement, and validate algorithms that aggregate complex, textual and graphical data into comprehensible descriptions of social networks
• Planning and coordination of data modeling & acquisition strategy, feature releases
• Close cooperation with the product team in translating planned product features into algorithms/metrics and vice versa
• Close cooperation with the development team in shaping our IT strategy and ensuring the robustness of production algorithms
• As a DS evangelist, you will familiarize other team members with our models to the extent and level of detail necessary for them

• We hire for ability, not credentials. You will notice that this is reflected in our recruiting process. The process is designed to test your ability to solve problems that you will face in the role you are applying for. There won’t be any brain teasers or anything else unrelated to what the job will be
• We invest tens of hours carefully crafting descriptions and the corresponding questions for each role. We spend so much time because we found this to be a good investment. These ads and their corresponding questions have proven to be an excellent filter. Make sure not to skip any questions – they are (by far) the most important part of the application
• If we like your answers, we will schedule the first interview. There are typically three interviews (+/-1) in total. For some roles, you may receive a take-home task that should take about 2-3 hours to complete. After that, we will ask you to work with us on a trial project for a week. We will pay you for this project. The idea is that you get to experience what it is like to work on our team, and we get a chance to experience what it would be like to have you as a colleague. Within that week, we will either make you an offer or let you know this is not a fit
• We keep this process to 2-3 weeks from when we get in touch with you