2 Π΄Π½Ρ Π½Π°Π·Π°Π΄
Data Scientist (AI)
ΠΡΡΡ & Π‘ΠΎΠΏΡΠΎΠ²ΠΎΠ΄
ΠΠ»Ρ ΠΌΡΡΡΠ° Ρ ΡΡΠΎΠΉ Π²Π°ΠΊΠ°Π½ΡΠΈΠ΅ΠΉ Π½ΡΠΆΠ΅Π½ Plus
ΠΠΏΠΈΡΠ°Π½ΠΈΠ΅ Π²Π°ΠΊΠ°Π½ΡΠΈΠΈ
Π’Π΅ΠΊΡΡ:
TL;DR
Data Scientist (AI) (Causal Inference/Pricing): Designing causal-uplift measurement frameworks and experimentation approaches to quantify the incremental impact of pricing models, with an accent on multidimensional data discovery and business-oriented ML evaluation. Focus on uplift modeling, A/B testing, translating airline business logic into technical pipelines, and communicating findings to technical and executive stakeholders.
Location: WrocΕaw, Poland
Company
builds transparent, AI-powered market models that provide demand predictions and real-time decision intelligence for commercial teams, initially serving the aviation industry.
What you will do
- Design and operationalize causal-uplift measurement frameworks for pricing models.
- Discover and analyze complex multidimensional data to generate actionable insights into pricing algorithms and their outcomes.
- Research and test novel approaches to uplift measurement and A/B testing.
- Collaborate with revenue managers, data analysts, and data engineers to encode airline business logic into models and technical pipelines.
Requirements
- At least 5 years of hands-on data analytics and data science experience, with a record of turning models into business insights.
- Proficiency in Python and common analytics and machine learning tools, including pandas, NumPy, scikit-learn, and statsmodels.
- Experience assessing the business performance and impact of machine-learning-powered systems.
- Proficiency in SQL and Git; BigQuery, Dataform, and GCP experience is an advantage.
- Strong communication, storytelling, stakeholder-management, and requirements-translation skills, including presenting to C-level executives.
- Bachelorβs or masterβs degree in economics, statistics, mathematics, or a related field; a PhD is an advantage.
Nice to have
- Domain knowledge in airlines, transportation, logistics, or vacations.
- Experience with causal inference, uplift modeling, anomaly detection, or pricing algorithms.
- Knowledge of mathematical optimization.
Culture & Benefits
- Self-driven, independent, and motivated approach to problem-solving.
- Collaboration across data science, revenue management, analytics, and engineering functions.
- Focus on supporting teammates and meeting product deadlines.
ΠΡΠ΄ΡΡΠ΅ ΠΎΡΡΠΎΡΠΎΠΆΠ½Ρ: Π΅ΡΠ»ΠΈ ΡΠ°Π±ΠΎΡΠΎΠ΄Π°ΡΠ΅Π»Ρ ΠΏΡΠΎΡΠΈΡ Π²ΠΎΠΉΡΠΈ Π² ΠΈΡ ΡΠΈΡΡΠ΅ΠΌΡ, ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΡ iCloud/Google, ΠΏΡΠΈΡΠ»Π°ΡΡ ΠΊΠΎΠ΄/ΠΏΠ°ΡΠΎΠ»Ρ, Π·Π°ΠΏΡΡΡΠΈΡΡ ΠΊΠΎΠ΄/ΠΠ, Π½Π΅ Π΄Π΅Π»Π°ΠΉΡΠ΅ ΡΡΠΎΠ³ΠΎ - ΡΡΠΎ ΠΌΠΎΡΠ΅Π½Π½ΠΈΠΊΠΈ. ΠΠ±ΡΠ·Π°ΡΠ΅Π»ΡΠ½ΠΎ ΠΆΠΌΠΈΡΠ΅ "ΠΠΎΠΆΠ°Π»ΠΎΠ²Π°ΡΡΡΡ" ΠΈΠ»ΠΈ ΠΏΠΈΡΠΈΡΠ΅ Π² ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΡ. ΠΠΎΠ΄ΡΠΎΠ±Π½Π΅Π΅ Π² Π³Π°ΠΉΠ΄Π΅ β
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