Data Analyst [rekrutacja online]
Localization: Wrocław
Daily activities
Network & Performance Engineering department provides in-depth analysis of worldwide telecommunications networks. As a Data Analyst you will have a key role in crafting the knowledge from raw data and creating the insights about future of telecom industry. You would be responsible for building new algorithms and designing mathematical models to crack the problems that are far beyond classical approaches.
We work with:
- Python for data processing and visualization (e.g. Pandas, NumPy, Matplotlib, Jupyter notebooks)
- Machine Learning frameworks
- Large datasets stored in relational and non-relational databases (e.g. PostgreSQL, MongDB, Cassandra)
- Data processing: Spark, Hadoop
- Other: Airflow, GIT and code review system
- Data handling, analytics and visualization skills (Python/R/Matlab)
- Master’s or Bachelor’s degree in Mathematics/Statistics, Computer Science, Telecommunication, or similar fields
- Experience in Python programming and familiarity with data science libraries (e.g., Jupyter, NumPy, Pandas, Bokeh, scikit-learn)
- Knowledge of basic concepts in statistics (random variables, central tendency, dispersion, statistical significance)
- Solid understanding of classical ML techniques (clustering, classification, regression)
- Knowledge of specific areas of Data Science (e.g., neural networks, bayesian learning, time series analysis)
- Ability to build and validate new algorithms
- Familiarity with relational databases and SQL
- Experience in working with ETL pipelines (e.g., Apache Airflow) is an additional plus
- Experience in working with large data sets and dedicated frameworks (e.g. Hadoop) is an additional plus
- High passion about data, critical thinking and problem-solving skills; data-driven mindset
- Good presentation and teamwork skills
- Good communication in English (both written and spoken)
- Ability to work independently and pro-active attitude. Creative thinkers are highly welcome.
Don’t have experience in something listed? We don’t mind if you’re a quick study!
