-6+ years of experience in the development of machine learning models and advanced analytics solutions.

-3+ years of experience in analyzing large-scale structured and unstructured data from multiple sources. -2+ years of strong proficiency in Python, R, or similar programming languages.

-Hands-on experience with ML libraries (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch).

-Solid knowledge of SQL and experience working with large-scale data infrastructure (e.g., Spark, Hadoop, Snowflake).

-Experience with data visualization tools (e.g., Tableau, Power BI, Plotly).

-Collaborate with product, engineering, and business teams to understand requirements and translate them into analytical solutions.

-Experience deploying models in production environments (e.g., using Docker, MLflow, or cloud services like AWS/GCP/Azure) and monitor their performance..

-Research and stay up to date on the latest data science techniques, tools, and best practices.

-Bachelor’s or Master’s in Computer Science, Statistics, Mathematics, Data Science, or a related field. Bonus points:

-Familiarity with MLOps practices and tools.

-Experience leading data science projects end-to-end.