Top Selection
Data Scientist
from 300,000 to 320,000 ₽ per month
Work format: remote possible
☑️ Responsibilities
- Selection and construction of suitable mathematical models for solving assigned tasks
- Selection of optimal solution architecture for product tasks
- Identification and elimination of product weaknesses
- Search for product growth points
- Synthesis of optimal mathematical models for solving product tasks
- Close interaction with business stakeholders, consultants, and the team
- Planning and conducting A/B/A/B/N experiments
- Maintaining the product's codebase and keeping it at a consistently high level
- Assigning tasks and monitoring their execution by other analysts
- Approving task solutions with management
- Presenting and defending results
- Mentoring Junior + Middle
☑️ Our requirements for candidates
- Specialized education / relevant certificates in data analysis and machine learning specializations
- At least 3 years of experience in data science
- Python (PEP 8)
- Ability to write code according to specified quality standards
- Knowledge of standard algorithms and data structures
- Good command of libraries for data analysis, numerical methods
- Ability to write code optimal in time and memory
- Algorithm complexity - debugging and code optimization
- Test-driven development
- Fluent in OOP
- Experience in project architecture design
- Designing process schedules (airflow, cron)
- Deploying projects to production
- Experience with CI/CD
- Working with data: SQL at a basic level (join, group by)
- Experience with relational databases
- Experience with PySpark (broadcast join, etc., Spark UI)
- Be skeptical of data, verify its correctness before use
- Ability to implement any query
- Knowledge of window functions
- Ability to identify non-optimal queries
- Knowledge of the advantages and disadvantages of various database types
- Experience developing ETL pipelines
- Ability to design database structures
- Ability to work with query plans
- Transactions/ACID/Indexes
- Familiar with basic probability theory and statistics
- Familiar with the concepts of A/B testing and hypothesis testing
- Ability to solve simple problems in probability theory, statistics, logic
- Knowledge of classical ML methods
- Knowledge of the full cycle of A/B testing
- Advanced command of hypothesis testing apparatus: multiple hypothesis testing, parametric/non-parametric methods, bootstrap
- Study and implementation of advanced ML models: Bayesian models / PGM / VBI, RL, etc.
- Knowledge of methods for reducing variance in experiments
- Possess intuition for data noise and identifying independent groups
- Ability to analyze effects without control and test groups
- Experience writing articles, presenting at conferences
- Experience with well-defined tasks
- Experience building analytical reports with specified requirements
- Experience presenting analytical research, verified hypotheses, etc.
- Deep understanding of product metrics: understanding key product metrics and their specifics, translating business tasks into DS/DA/DE and decomposing complex business tasks, building proxy product metrics
- Ability to formulate new research directions
- Ability to identify weak/strong aspects of product business logic
- Experience in consulting and working closely with product managers or business stakeholders
- Experience in decomposing business goals into analytical stories, estimating task completion times
- Ability to assign tasks to mid-level developers
Stack: Python; SQL; data visualization (matplotlib, seaborn, plotly / BI tools); Git; PyTest; Spark 2.2+; Grafana/Airflow; Docker; Kubernetes (K8S)
Contacts: info@top-selection.ru
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