Data Scientist, DoubleVerify

• This position will combine analytical rigor, a relentless curiosity, a strong knowledge of statistical methods and experience in implementing them
• MS degree in applied mathematics (e.g., statistics, probabilities, operations research, machine learning)
• 2 years experience as a Data scientist with actual algorithms implementation in an industry programming language (eg Python, C++...)
• Python
• SQL
• Kubernetes, Docker, Github
• Google Cloud Environment, App Engine Standard, Cloud SQL, Google Cloud Datastore..
• Do things only once. No repetitive task survives ingenuity and automation: at Scibids, everything needs to scale!
• Base your decisions on data points. Preconceived personal convictions rarely survive thorough confrontation with actual data
• Work in a team and be curious. Every Scibids member has stock-options and is focused on the same objective: make Scibids the next adtech unicorn! This means being interested in how one’s daily personal work fits in Scibids general strategy and having in mind the greater good of the company rather than individual accomplishments
• Have a good laugh. We are a young, hard-working team with huge ambitions: nothing wipes off long hours of work better than sharing a drink with the team!

Desirable

• The mission of Scibids is to provide media buyers with fully automated buying strategies for display campaigns, leading to uncompared performances for a minimum of human work
• As a DataScientist, your role will be to evaluate and improve "Scibids DoubleVerify" bidding algorithms, which are Scibids main asset, and to actively participate into Scibids automation and development process: each business case not yet automatically handled by our product should be met by the corresponding product improvement
• This position will combine high development standards, a relentless curiosity, a strong understanding of business priorities and the ambition for your work to become a real game changer!
• Working with massive datasets (billions of ads impressions/month) and millions of variables
• Solving non-routine analysis problems (not handled by off-the-shelf ML solvers)
• Solving challenging scaling/engineering problems as our system produces thousands of ML models per day
• Working closely with the commercial and customer success team and help identify the business cases where a new algorithm is needed/existing ones need improvement
• Identify and automate any repetitive process taking place at Scibids, including cases where this means developing some AI routines replacing “human common sense”
• Contract type: full-time position (French “CDI”)

• Preferred availability: ASAP