About the Role
We are hiring a Data Scientist who is passionate about solving complex business problems using data, machine learning, and AI. The ideal candidate has a strong foundation in Python, hands-on experience with ML frameworks, and exposure to Microsoft Azure cloud services. You will work on developing scalable ML models, deploying AI solutions, and deriving actionable insights from large datasets.

Key Responsibilities
- Design, build, and evaluate machine learning models for classification, regression, forecasting, and NLP use cases.
- Develop and maintain data pipelines using Python and Azure Data Factory / Azure Databricks for ETL and feature engineering.
- Deploy ML models on Azure Machine Learning (Azure ML) using endpoints, pipelines, and MLflow tracking.
- Collaborate with data engineers to ensure data quality, availability, and governance across Azure Data Lake and Azure Synapse Analytics.
- Apply AI/GenAI capabilities (Azure OpenAI, Cognitive Services) to build intelligent applications and automation workflows.
- Monitor model performance in production,



identify drift, and implement retraining strategies.
- Translate business requirements into data science problem statements and communicate findings to stakeholders.
- Participate in code reviews, documentation, and adherence to ML Ops best practices.

Required Skills & Qualifications
- Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, or related field.
- 4+ years of professional or project-based experience in data science or machine learning.
- Robust proficiency in Python (pandas, NumPy, scikit-learn, XGBoost, LightGBM).
- Hands-on experience with Microsoft Azure services: Azure ML, Azure Databricks, Azure Data Factory, Azure Blob Storage, or Azure Synapse.
- Understanding of supervised and unsupervised learning algorithms, model evaluation, and hyperparameter tuning.
- Experience with deep learning frameworks: TensorFlow or PyTorch (at least one required)

📌 Data Scientist II (India)
🏢 Johnson Controls
📍 India