Senior Data Scientist (Dynamic Promo - Quick Commerce)

TL;DR

Senior Data Scientist (Dynamic Promo - Quick Commerce): Building and deploying classical ML and uplift/personalization models to improve affordability perception and user experience at global scale, with an accent on causal inference, time-series forecasting of incentive supply/demand, and productionizing experimentation-driven uplift models. Focus on leading end-to-end data science initiatives, running A/B tests on customer-facing uplift models, and collaborating with MLEs and engineers to deliver scalable, observable solutions.

Location: Berlin, Germany

Company

hirify.global is a local delivery platform operating across multiple countries, headquartered in Berlin.

What you will do

• Design, experiment, and deploy classical ML and uplift models (including personalization) to measurably improve affordability perception and user experience.
• Independently lead end-to-end data science initiatives from technical design and implementation to stakeholder communication.
• Drive experimentation by formulating hypotheses, analyzing A/B tests, and turning insights into production-ready targeting and incentive deployment.
• Apply advanced time series and causal inference techniques to model and forecast supply and demand of incentives.
• Use live user signals and context to make affordability interventions adaptive and dynamic.
• Collaborate with MLEs and engineers to ensure solutions are scalable, reliable, and fast in production, and mentor peers to raise the quality bar.

Requirements

• 5+ years of industry experience applying data science and machine learning in production, ideally for large-scale consumer-facing applications.
• Expertise in causal inference and uplift modeling for user targeting and intervention strategies, plus time series analysis.
• Strong statistical foundations and ability to separate signal from noise in large-scale experimentation and A/B testing.
• Excellent engineering skills: clean, maintainable Python code and experience bringing ML models into production with observability and monitoring.
• Proven ability to lead independently and work cross-functionally with engineers and product stakeholders.
• Hands-on, pragmatic “hacker mentality” with comfort iterating quickly to get solutions live.

Culture & Benefits

• Hybrid working model with face-to-face collaboration in the Berlin campus 2 days a week.
• 27 days holiday plus an extra day on the 2nd and 3rd year of service.
• €1,000 educational budget, language courses, parental support, and access to Udemy Business.
• Health checkups, meditation & gym, plus life & accident insurance and a corporate pension plan.
• Employee Share Purchase Plan, sabbatical bank, public transportation ticket discount, and meal vouchers.

Hiring process

• Apply and go through recruiter screening.
• Interview process includes evaluation of technical and collaboration fit.
• Final steps include interview preparation guidance and common interview Q&A support.