Senior Data Scientist – Marketing Measurement & Causal Inference (m/f/d)

FlixBus; Lisboa; Sur place; EUR 70 000 - 100 000; Plein temps

Avantages offerts par ce poste

Work from (M)Anywhere: up to 60 days/2

Hybrid work model

Wellbeing support

Learning & Development

Mentoring Program

Résumé du poste

Flix is seeking a Senior Data Scientist to own the design, execution, and evolution of causal measurement practices across global markets. You will run geo- and time-based experiments, apply advanced causal inference methods, and shape how marketing investment is allocated.

You will lead a test-and-learn program for paid channels, advance attribution models like CLV-MTA and MMM, and translate findings into strategic guidance for marketing, finance, and senior leadership.

Qualifications

• Master's or PhD in a quantitative field (Statistics, Econometrics, Applied Mathematics, Data Science).
• 5+ years in data science or quantitative research with causal-experiment focus.
• Strong command of causal inference methods (DiD, synthetic control, Bayesian time series).

Responsabilités

• Design and run geo-based, time-based, and synthetic control experiments for global markets.
• Apply causal inference techniques to measure incremental marketing impact on bookings and revenue.
• Build and manage a structured test-and-learn program across paid channels for value.
• Contribute to attribution models (CLV-MTA, MMM) and provide benchmarks.
• Translate complex causal findings into actionable recommendations for stakeholders.

Connaissances

Python

SQL

Power BI

Statsmodels

PyMC

CausalImpact

Git

BigQuery

Snowflake

causal inference

Formation

Master's or PhD in Statistics/ Econometrics/ Applied Mathematics/ Data Science

Outils

Statsmodels

PyMC

CausalImpact

BigQuery

Snowflake

Description du poste

At Flix, we offer a dynamic work environment with competitive pay, strong growth opportunities, and a tech-driven approach to making travel more accessible, sustainable, and affordable.

As a Senior Data Scientist in our Commercial & Marketing Intelligence team at Flix, you can make an impact by owning and evolving our causal measurement practice — designing and running experiments that directly shape how we allocate our global marketing budget. You will work closely with a dedicated team across Marketing & Sales, Revenue Management, Reporting, and Engineering to ensure our incrementality evidence drives smarter, more transparent choices at scale.

About the Role

• Own the design, execution, and continuous improvement of geo-based, time-based, and synthetic control experiment frameworks, ensuring methodological rigour and scalability across global markets and channels
• Apply econometric and causal inference techniques — including difference-in-differences, synthetic control, and Bayesian structural time series — to measure the true incremental effect of marketing activities on bookings and revenue
• Build and manage a structured test-and-learn programme across paid channels, identifying measurement gaps and prioritising experiments by expected business value
• Contribute to the development and validation of attribution models (CLV-MTA and MMM), providing reliable benchmarks that reduce reliance on platform self-reported data
• Translate complex causal findings into clear, actionable recommendations for a wide range of stakeholders including marketing teams, finance, and senior management
• Review experiment designs, create thorough documentation, and help shape internal standards for how Flix measures marketing effectiveness across all channels

About You

• Holds a Master's or PhD in Statistics, Econometrics, Applied Mathematics, Data Science, or a related quantitative field
• Brings 5+ years of experience in a data science or quantitative research role, with hands‑on expertise in designing and evaluating causal experiments such as geo experiments, time-series holdouts, or synthetic control studies
• Demonstrate strong command of causal inference methods including difference-in-differences, synthetic control, Bayesian structural time series, or matched market testing
• Proficient in Python,SQL, Power BI and experienced with statistical modelling libraries such as statsmodels, PyMC, CausalImpact, or equivalent tools
• Comfortable with version control (Git), reproducible workflows, and cloud or data warehouse environments such as BigQuery or Snowflake
• Proven ability to present statistical findings to non-technical audiences and contribute to strategic choices with data
• Experience in marketing measurement, media mix modelling, or growth reporting is a plus — as is familiarity with Bayesian methods

We recognize that everyone carries a unique set of valuable skills and experiences. If you think you could have an impact even though you don't meet 100% of the requirements, we still encourage you to apply. We want to hear from you!

What We Offer

• Work from (M)Anywhere: Depending on your role, work from another location for up to 60 days per year.
• Hybrid work model: We are an office-first company, but we offer flexibility to balance work and life.
• Wellbeing support: Access confidential 1:1 counselling, courses, and stress management for yourself and up to four family members.
• Learning & Development: Take advantage of language classes, training courses, and expert-led sessions to grow your skills.
• Mentoring Program: Connect with experienced colleagues to gain insights and accelerate your career.

At Flix, you’ll find teams that rally together to overcome challenges and spark creativity. We believe in ownership culture - giving you the freedom to take initiative, make an impact, and shape your own career path.
As we continue to expand across the globe, you can make a real difference in how we work.

If you’re ready to grow and lead your journey, Flix is the place for you!

At Flix, we are committed to fostering diversity and inclusion. To support this initiative, we invite all applicants to complete our demographic questions on voluntary basis. Your responses will be processed as anonymized data and not linked to your profile, and thus assessed for statistical purposes and internal research.

If you prefer not to provide this information, simply click on "I do not wish to answer." Be assured that neither the decision not to participate nor your answers will have an impact on your application, and your answers will remain anonymous and unidentifiable to you individually. The decision on your application will be made independently from your participation and the information you provide.