Senior Data Scientist
⚲ Warszawa, Gdańsk, Wrocław, Kraków, Poznań, Łódź, Lublin, Szczecin, Olsztyn, Białystok
19 320 - 23 520 PLN netto (B2B)
Wymagania
- Data Science
- Python
- PySpark
- SQL
Opis stanowiska
About the Role
We’re looking for a Senior Data Scientist to own and deliver high-impact data products from concept to production. You’ll bridge the gap between business needs and production-grade ML, with a special focus on enhancing user experience through advanced personalization and measuring true business impact using causal inference.
What You’ll Do
•
Discover: Partner with business leaders to translate complex challenges into actionable ML hypotheses.
• Build & Scale: Design, develop, and deploy hands-on recommender engines, advanced classification models, and NLP solutions using large-scale datasets.
• Measure Impact: Apply Uplift modeling techniques to move beyond correlation and measure the genuine incremental impact of our products and campaigns.
What You Bring (Core Tech Focus)
•
5+ years of commercial experience as a Data Scientist delivering end-to-end products.
• Specialized ML Expertise:
• Proven experience building and optimizing Recommender Systems (at scale).
• Hands-on knowledge of Causal Inference, specifically Uplift Modeling.
• Deep understanding of supervised learning, focusing on complex Classification models.
• Solid background in Natural Language Processing (NLP) and Embeddings knowledge.
•
Tech Stack: Python(Pandas, Scikit-learn, PyTorch/TF), PySpark, SQL.
• Cloud & Infrastructure: Hands-on experience with Databricks, AWS, GCP, Azure, or Snowflake.
Nice to Have
• Background in Management Consulting or Marketing Analytics.
• Experience with Kedro, CI/CD, or CLI tools (Bash/Zsh).
We’re looking for a Senior Data Scientist to own and deliver high-impact data products from concept to production. You’ll bridge the gap between business needs and production-grade ML, with a special focus on enhancing user experience through advanced personalization and measuring true business impact using causal inference.
What You’ll Do
•
Discover: Partner with business leaders to translate complex challenges into actionable ML hypotheses.
• Build & Scale: Design, develop, and deploy hands-on recommender engines, advanced classification models, and NLP solutions using large-scale datasets.
• Measure Impact: Apply Uplift modeling techniques to move beyond correlation and measure the genuine incremental impact of our products and campaigns.
What You Bring (Core Tech Focus)
•
5+ years of commercial experience as a Data Scientist delivering end-to-end products.
• Specialized ML Expertise:
• Proven experience building and optimizing Recommender Systems (at scale).
• Hands-on knowledge of Causal Inference, specifically Uplift Modeling.
• Deep understanding of supervised learning, focusing on complex Classification models.
• Solid background in Natural Language Processing (NLP) and Embeddings knowledge.
•
Tech Stack: Python(Pandas, Scikit-learn, PyTorch/TF), PySpark, SQL.
• Cloud & Infrastructure: Hands-on experience with Databricks, AWS, GCP, Azure, or Snowflake.
Nice to Have
• Background in Management Consulting or Marketing Analytics.
• Experience with Kedro, CI/CD, or CLI tools (Bash/Zsh).
🔍 Dekoder Ogłoszenia
🔴
own and deliver high-impact data products from concept to production
Oczekuje się, że będziesz samodzielnie prowadzić projekty od pomysłu do wdrożenia, co może oznaczać dużą odpowiedzialność i presję.
🟡
bridge the gap between business needs and production-grade ML
Może to oznaczać, że będziesz musiał tłumaczyć skomplikowane wymagania biznesowe na język techniczny i odwrotnie, co wymaga dobrych umiejętności komunikacyjnych i zrozumienia obu stron.
🟡
special focus on enhancing user experience through advanced personalization
Choć brzmi to pozytywnie, może oznaczać, że główny nacisk będzie położony na tworzenie systemów rekomendacyjnych i personalizacji, a inne obszary Data Science mogą być mniej priorytetowe.
🟢
measuring true business impact using causal inference
Wymaga to zaawansowanych umiejętności statystycznych i analitycznych, a nie tylko budowania modeli.
🔴
5+ years of commercial experience as a Data Scientist delivering end-to-end products
Wymagane jest doświadczenie w samodzielnym prowadzeniu projektów od początku do końca, a nie tylko w pracy nad poszczególnymi etapami.