Senior Data Science Consultant with Python
⚲ Kraków
22 848 - 29 064 PLN (B2B)
Wymagania
- Python
- pandas
- SQL
- Relational database
- Machine Learning
- NumPy
- AI
- LLM
- ML
- Big Data (nice to have)
- PySpark (nice to have)
- Cloud platform (nice to have)
- AWS (nice to have)
- MLOps (nice to have)
- Data pipelines (nice to have)
- Data visualization (nice to have)
- Matplotlib (nice to have)
- GCP (nice to have)
- Azure (nice to have)
- Seaborn (nice to have)
- Plotly (nice to have)
Opis stanowiska
O projekcie:
As a Data Analyst, you will design and develop data-driven solutions that help transform complex datasets into meaningful insights and business value. Working with Python, SQL, and modern analytics tools, you will analyze data, build machine learning models, and support data-informed decision-making across the organization.
You will collaborate closely with business and technical stakeholders to deliver reliable, high-quality analytical solutions while continuously improving data processes, methodologies, and best practices.
Wymagania:
Must have- Hands-on experience with Python for data analysis and data processing.- Strong knowledge of data manipulation and analysis using Pandas and NumPy.- Good understanding of SQL and working with relational databases.- Basic knowledge of Machine Learning concepts and workflows.- Experience with data wrangling, cleansing, and feature engineering.- Strong analytical thinking and problem-solving skills.- Experience working with structured and unstructured datasets.- Ability to translate data into actionable insights and business value.- Basic understanding of LLMs and Generative AI solutions.Nice to have- Experience with Big Data technologies such as PySpark or similar frameworks.- Familiarity with cloud platforms such as GCP, AWS, or Azure.- Experience with prompt engineering, RAG, or AI-powered applications.- Exposure to MLOps practices and model deployment.- Knowledge of data pipelines and data engineering concepts.- Experience with data visualization tools such as Matplotlib, Seaborn, or Plotly.- Experience working in regulated environments such as finance or banking.Don't worry if you don't tick every box
We're looking for curious and analytical professionals who enjoy working with data and solving complex problems. If you meet most of the requirements and are excited about the opportunity, we encourage you to apply. We value learning agility, critical thinking, and a growth mindset as much as experience with specific technologies.
Codzienne zadania:
- Design and develop data processing and analytical solutions in Python
- Work with datasets to clean, transform and analyse data
- Build and optimize machine learning models
- Translate business requirements into data-driven solutions
- Collaborate with stakeholders and engineering teams
- Ensure quality, performance and reliability of data solutions
- Contribute to continuous improvement of data practices
As a Data Analyst, you will design and develop data-driven solutions that help transform complex datasets into meaningful insights and business value. Working with Python, SQL, and modern analytics tools, you will analyze data, build machine learning models, and support data-informed decision-making across the organization.
You will collaborate closely with business and technical stakeholders to deliver reliable, high-quality analytical solutions while continuously improving data processes, methodologies, and best practices.
Wymagania:
Must have- Hands-on experience with Python for data analysis and data processing.- Strong knowledge of data manipulation and analysis using Pandas and NumPy.- Good understanding of SQL and working with relational databases.- Basic knowledge of Machine Learning concepts and workflows.- Experience with data wrangling, cleansing, and feature engineering.- Strong analytical thinking and problem-solving skills.- Experience working with structured and unstructured datasets.- Ability to translate data into actionable insights and business value.- Basic understanding of LLMs and Generative AI solutions.Nice to have- Experience with Big Data technologies such as PySpark or similar frameworks.- Familiarity with cloud platforms such as GCP, AWS, or Azure.- Experience with prompt engineering, RAG, or AI-powered applications.- Exposure to MLOps practices and model deployment.- Knowledge of data pipelines and data engineering concepts.- Experience with data visualization tools such as Matplotlib, Seaborn, or Plotly.- Experience working in regulated environments such as finance or banking.Don't worry if you don't tick every box
We're looking for curious and analytical professionals who enjoy working with data and solving complex problems. If you meet most of the requirements and are excited about the opportunity, we encourage you to apply. We value learning agility, critical thinking, and a growth mindset as much as experience with specific technologies.
Codzienne zadania:
- Design and develop data processing and analytical solutions in Python
- Work with datasets to clean, transform and analyse data
- Build and optimize machine learning models
- Translate business requirements into data-driven solutions
- Collaborate with stakeholders and engineering teams
- Ensure quality, performance and reliability of data solutions
- Contribute to continuous improvement of data practices
🔍 Dekoder Ogłoszenia
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design and develop data-driven solutions that help transform complex datasets into meaningful insights and business value
Oczekuje się, że będziesz samodzielnie tworzyć i wdrażać rozwiązania analityczne, które przyniosą wymierną korzyść biznesową.
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collaborate closely with business and technical stakeholders
Będziesz musiał dużo komunikować się z różnymi zespołami, co może oznaczać częste spotkania i potrzebę tłumaczenia złożonych zagadnień technicznych na język biznesowy.
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continuously improving data processes, methodologies, and best practices
Może to oznaczać, że obecne procesy nie są zoptymalizowane i będziesz musiał je usprawniać od podstaw.
🔴
Basic knowledge of Machine Learning concepts and workflows
Zakres obowiązków związanych z ML może być ograniczony do podstawowych zadań, a nie zaawansowanego modelowania.
🔴
Ability to translate data into actionable insights and business value
Oczekuje się, że nie tylko będziesz analizować dane, ale także aktywnie proponować i wdrażać rozwiązania biznesowe oparte na swoich odkryciach.