Head of Data
At StuDocu we believe in one thing: setting knowledge free will help humanity overcome its greatest challenges. StuDocu is the world’s leading community for university students. Every month we help more than 15 million university students to get smarter, faster. Being active in over 60 countries already and accelerated by a recent investment of 50 million USD, we are well on our way to completing our mission of supporting all higher education students around the globe!
As the newly appointed Head of Data Science you will work tirelessly to raise the data science efforts at StuDocu to the next level.
You have many different stakeholders to manage within the company, each with unique challenges. For instance, you may work with one of the product managers to figure out how we can run a robust recommendation engine to help students find relevant courses. Together with our VP of Growth, you might look in the data for growth opportunities. How can we leverage the 15 million users a month into growing faster and helping more students? Our COO may request your help in solving some final problems in our LTV prediction models. All the while you’ll also try to help out the operations team to better process uploaded documents by predicting which content is relevant and which documents are better removed from the platform.
To be able to deliver on these and so many other projects that involve data you get to manage and build your team of data scientists, data engineers and data analysts. You will hire them and coach them to deliver the most possible value to our business and our users.
Responsibilities and Duties:
- Leading our data science team, you hire, coach and manage the data scientists and engineers in your team.
- Setting the data science strategy and defining the quarterly goals of the team through the OKRs.
- Being the linking pin between Business Strategy and Data Execution.
- Designing intelligent and creative data science solutions to solve complex business problems. Starting simple, delivering value early and iterating with milestones.
- Mentoring other Data Scientists on the team by building a strong culture of Data Science best practices and ensuring that we pick the right tools (and techniques) for the right job.
- Act as Data Science liaison/gatekeeper for stakeholders in the company. Interact directly with the Management Team, Product Managers, Developers and other teams to build a strong understanding of how StuDocu operates and the Data Science opportunities/challenges ahead.
Why you are going to love it here:
- You will build our data team. You get to determine the future of the DS team and make the hiring decisions.
- We have huge datasets that house many insights that are waiting to be uncovered. We have over 300 million pages across the 10 million documents on the platform. With 15 million users accessing them every month. By exploring this mountain of data you will bring our users an even more amazing experience and invaluable insights to the team.
- Since our very early days, StuDocu has already been a data-driven company. We realise the importance of data and the opportunities that it can unlock. It will be easy to get support for your initiatives.
*During the COVID-19 pandemic, we are still interviewing and hiring, but all conversations will obviously be via video call! For now, StuDocu adopted a flexible remote-first policy, but we still require our 70+ employees to be located in or near Amsterdam in the Netherlands. We encourage our employees to visit the office once every other week to build relationships and socialize while abiding by the safety rules. When it's safe again, you will be able to take full advantage of our bright office in the center of Amsterdam with canals, restaurants, and cafes right around the corner.
- Bachelor's degree (or higher) in Data Science, Mathematics, Computer Science, Physics or equivalent.
- 6+ years of experience in Data Science and/or Machine Learning roles (past experience as a team lead at a Tech company desired).
- Strong background both on Machine Learning as well as Data Engineering.
- Prior experience with Machine Learning techniques in all three areas: supervised, unsupervised and reinforcement learning.
- Strong SQL skills; Proficiency using Python and popular DS libraries.
- Experience working with a modern Data Warehouse like Redshift, Snowflake or BigQuery, and using BI tools like Metabase, Mode or Looker.
- Solid English communication skills, both written and verbal.
- Team-player with strong peer-influence skills able to be a credible voice towards all areas of our business.
- Being able to translate data findings into business opportunities.