Requirements
### Requirements
- Relevant education/certifications in data analysis and machine learning.
- 2+ years of experience in data science.
- Proficient in Python (PEP 8).
- Ability to write optimal code in terms of time and memory.
- Debugging and code optimization skills.
- Development through testing.
- Strong understanding of OOP.
- Basic SQL skills (join, group by).
- Experience with relational databases.
- Experience with PySpark (broadcast join, Spark UI).
- Knowledge of window functions.
- Ability to identify non-optimal queries.
- Familiarity with basic probability theory and statistics.
- Understanding of A/B testing concepts and hypothesis testing.
- Ability to solve simple problems in probability theory, statistics, and logic.
- Knowledge of classical ML methods.
- Understanding the full cycle of conducting A/B tests.
- Proficiency in hypothesis testing methods: multiple hypothesis testing, parametric/non-parametric methods, bootstrap.
- Study and implementation of advanced ML models: Bayesian models, PGM, VBI, RL, etc.
- Presentation of analytical findings and validated hypotheses.
- Understanding of key product metrics and their features, translating business tasks into DS/DA/DE, and decomposing complex business tasks into proxy metrics.