Product Data Scientist

Key Skills

Data science techniques, Effective communication skills, JAX framework, Machine learning techniques, Planning and organization, PyTorch

Job Description

• Product Data Scientists collaborate closely with Product Managers and our product squads in order to provide advanced analytics support, help define metrics and measurement procedures, identify high-impact opportunities, lead the experimentation process and much more
• As part of the broader Data family, they also engage with other data scientists and engineers to constantly upskill and learn from each other, share best practices and generally foster a culture of excellence.

On your first month in Fever:

• You’ll be fully integrated into the Data organization, including familiarizing yourself with our data infrastructure
• You'll build a significant understanding of our product including key metrics and challenges
• You’ll get familiar with Fever’s tech stack and frameworks for backend and frontend development and experimentation
• You’ll attend some of the Fever Original’s experiences like Candlelight

After 3 months in Fever:

• You'll understand the full business context at Fever and will be able to identify new challenges where your skills can eventually make a difference
• You'll have established a solid partnership with Product Managers and will be consistently providing new insights and hypotheses
• You'll have owned at least one experiment, from metric definition to analysis and follow-up definition.
• You’ll participate in some of the hackdays or hackathons we organize with other teams

On your 6th month in Fever:

• You'll be driving improvements to our experimentation capabilities to enable us to efficiently and rigorously test even more hypothesis and build a world-class product
• You’ll be mentoring other new joiners to the team and be an active contributor to the data science and analytics community at Fever, promoting best practices and fresh ideas to make the whole community more efficient
• You’ll have significant input in the planning of the Data Science org and will also be able to influence our partners' roadmaps

About you

• You have solid math, statistics and Machine Learning fundamentals (typically MSc or PhD level) 
• You pay extreme attention to detail and are motivated by the idea of deep-diving into complex data coming from a product used by millions of people across the world
• You have experience designing and evaluating randomized experiments (e.g. A/B tests), ideally in a digital product scenario
• You have an entrepreneurial spirit, get stuff done and thrive in a fast paced environment so you
  • Take ownership of your work
  • Communicate early and often
  • Take controlled risks
  • Leave things better than you found them
• You are comfortable with software engineering best practices and write robust, reproducible and maintainable code, but can also build quick prototypes to validate ideas and enable new analysis.
• You have excellent communication skills and are proficient in business English

It would be a plus if you...

• Have practical experience with any of the following: personalization, time series forecasting, adaptive optimization (e.g. contextual bandits)
• Have relevant work experience in marketing or internet tech companies
• Have experience with current ML and scientific computing frameworks such as Pytorch, JAX, etc.

Benefits & Perks

• Attractive compensation package consisting of base salary and the potential to earn a significant bonus for top performance.
• Stock options.
• Opportunity to have a real impact in a high-growth global category leader
• 40% discount on all Fever events and experiences
• Home office friendly
• Responsibility from day one and professional and personal growth
• Great work environment with a young, international team of talented people to work with!
• Health insurance and other benefits such as Flexible remuneration with a 100% tax exemption through Cobee.
• English Lessons
• Gympass Membership
• Possibility to receive in advance part of your salary by Payflow.