Senior Data Scientist – Optimization & Machine Learning
I
ITELENCEData Science
Kraków, Wrocław, Warszawa, Poznań, Gdańsk, Country code: PLContractSenior
Salary25200 - 31920 PLN per hour b2b currencySource=original; 5409 - 6851 CHF per hour b2b currencySource=conversion; 5740 - 7271 EUR per hour b2b currencySource=conversion; 4935 - 6251 GBP per hour b2b currencySource=conversion; 6534 - 8276 USD per hour b2b currencySource=conversion
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Job Details
- Languages
- English (B2)
- Experience
- Minimum 8 years
- Required Skills
- PythonSQLMachine LearningAzureDatabricks
Requirements
- Minimum 8 years of experience in Data Science, Operations Research, or a related field.
- Strong knowledge of optimization methods, particularly MILP, VRP, and scheduling.
- Practical experience working with optimization solvers, specifically Gurobi.
- Very good proficiency in Python and SQL.
- Experience applying Machine Learning in practical business solutions.
- Experience building predictive models and performing feature engineering.
- Ability to integrate Machine Learning models with optimization solutions.
- Experience translating business problems into analytical and optimization models.
- Experience working with large datasets and data processing pipelines.
- Knowledge of cloud environments, especially Azure and Databricks.
- Ability to analyze and troubleshoot model performance and data quality issues.
- Good command of the English language (B2).
Responsibilities
- Design, develop, and optimize decision-making models using mathematical optimization, particularly MILP and heuristic methods.
- Solve optimization problems related to routing, scheduling, and resource allocation.
- Work with optimization solvers, specifically Gurobi.
- Utilize Machine Learning methods to support decision systems, including predictive modeling and feature engineering.
- Integrate Machine Learning models with optimization models to build comprehensive decision-support solutions.
- Translate business and operational requirements into analytical models and optimization problems.
- Analyze business constraints and identify trade-offs between costs, service levels, and operational feasibility.
- Diagnose and resolve model issues related to infeasibility, performance, and data quality.
- Design, develop, and maintain data processing pipelines using Python and SQL.
- Work with cloud environments, particularly Azure and Databricks.
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