Data Scientist

Experience Required:
Proficiency in DS algorithms for RNN, GNN networks, ML Flow, and knowledge of LLMs and embeddings.
Ability to develop production-grade prediction ML models from various data sources in Azure Blob/Databricks.
Experience with A/B testing to validate quantitative ML model improvements.
Tech stack: Azure, Databricks, Python (optional: R).
8 years of relevant experience in Python development in the Data Science domain.
Bachelor’s degree in a highly analytical discipline (Statistics, Economics, Computer Science, Mathematics, Operations Research, etc.).

Responsibilities:
Hands-on experience in Python development with a focus on Data Science & ETL.
Build CI/CD pipelines using Azure DevOps or similar tools.
SQL experience for data manipulation and analysis.
Test, validate, and automate data science models.
Collaborate with a team of data scientists, data engineers, and architects; document processes.
Requirements:
7-8 years of experience in end-to-end machine learning projects.
Advanced Python skills (Pandas, NumPy, Matplotlib, SciPy, SQLite 3, etc.).
Manage the entire Data Science life cycle, including data acquisition, cleaning, and statistical modeling.
Expertise in translating business requirements into analytical models and algorithms.
Familiarity with machine learning frameworks (TensorFlow, PyTorch, Keras, Scikit-Learn).
Knowledge of statistical methods (linear regression, confidence intervals).
Experience with API integration and data feeds from social analytics (Facebook, Instagram, Twitter).
Proficiency in Databricks, Azure DataLake Gen2, and Azure ML Services.
Ability to build Python & REST APIs for data integration