Data Scientist - Artificial Intelligence/Machine Learning

About the Role :

We are looking for an experienced Data Scientist to lead the design and development of AI/ML solutions leveraging Azure Machine Learning and Generative AI frameworks. The ideal candidate will have hands-on expertise in Python, PySpark, Azure ML, and OpenAI, with a proven track record of building, deploying, and optimizing data-driven models at scale.

Key Responsibilities :

- Lead the end-to-end development of AI/ML solutions from problem definition to model deployment and performance monitoring.

- Design and build statistical forecasting, optimization, and machine learning models to solve complex business problems.

- Develop and implement LLM-based and GenAI solutions leveraging OpenAI and Azure ecosystems.

- Utilize Azure Machine Learning, MLflow, and Azure Databricks for scalable experimentation and deployment.

- Perform data wrangling, cleaning, and analysis using Python, PySpark, and SQL.

- Collaborate with cross-functional teams to translate business challenges into analytical solutions.

- Ensure model explainability, reproducibility, and ethical AI practices throughout the model lifecycle.

- Present analytical findings and recommendations effectively to both technical and non-technical stakeholders.

Required Skills and Experience :

- 8 to 10 years of overall experience with at least 5 years of relevant experience as a Data Scientist.

- Strong proficiency in Python and PySpark.

- Experience with Azure Machine Learning, OpenAI, and SQL.

- Minimum 2 years of hands-on experience with Azure Cloud, Natural Language APIs, and MLflow.

- Proven experience with LLMs and GenAI frameworks.

- Strong background in statistical data analysis, forecasting, and optimization modeling.

- Proficiency in TensorFlow, PyTorch, and Scikit-learn.

- Excellent communication, collaboration, and problem-solving skills.

Good to Have :

- Experience working with Azure Databricks.

- Exposure to data engineering and pipeline automation in cloud environments.