Senior Data Scientist (Advertising)

Location: Berlin, Germany

Company

hirify.global develops data-driven travel technology, including a proprietary advertising platform for hotels, destinations, and airlines.

What you will do

• Design, build, and improve machine learning and statistical models for audience targeting, real-time bidding, campaign optimization, and budget allocation.
• Research optimization strategies using AI and classical machine learning to improve campaign performance and bidding efficiency.
• Forecast supply and demand dynamics to improve advertising decisions and budget utilization.
• Develop experimentation frameworks, A/B tests, success metrics, and data-driven model evaluations.
• Deploy machine learning solutions to production and establish monitoring, feedback loops, and model governance.
• Collaborate with data engineers, software engineers, product managers, and business stakeholders while mentoring other data scientists and influencing technical roadmaps.

Requirements

• Strong knowledge of statistics, experimentation, machine learning, data wrangling, model validation, and performance evaluation.
• Strong software engineering fundamentals with production experience in Python and SQL.
• Experience deploying, operating, and monitoring machine learning systems in production.
• Proven ability to deliver complex projects from concept to production with strong ownership.
• Excellent communication, problem-solving, and cross-functional collaboration skills.
• Commitment to quality, reliability, correctness, curiosity, and pragmatic data-driven decision-making.

Nice to have

• Hands-on experience with GCP and BigQuery.
• Experience in programmatic advertising, ad tech, or related optimization domains.
• Experience building or operating real-time machine learning systems.
• Familiarity with large-scale experimentation and online optimization techniques.

Culture & Benefits

• Inclusive workplace focused on belonging, fair treatment, and equal opportunity.
• Opportunity to work with microservices, large-scale data, real-time decision-making, and rapid experimentation.
• Collaboration across data science, engineering, product, and business functions.