Software Engineer - Data Scientist

Johnson Controls; Pune District; Hybrid; INR 1,500,000 - 2,100,000; Full time

Benefits offered by this job

Azure certification sponsorship

Mentorship from senior data scientists

Flexible hybrid working model

Job summary

Johnson Controls seeks a Junior Data Scientist to solve business problems with data, ML, and AI. You will develop scalable models, deploy AI solutions, and extract insights from large datasets in a hybrid/on-site setup.

The role requires 4–7 years of data science experience, strong Python skills, and hands-on Azure experience. You will collaborate across teams, optimize ML workflows, and contribute to governance and MLOps practices.

Qualifications

• Bachelor's or Master's in CS/DS/Engineering/Mathematics.
• 4–7 years of data science or ML experience.
• Strong Python proficiency (pandas, NumPy, scikit-learn, XGBoost, LightGBM).
• Hands-on with Microsoft Azure: Azure ML, Databricks, Data Factory, Blob Storage, Synapse.
• Understanding of supervised/unsupervised learning, model eval, hyperparameter tuning.
• Experience with TensorFlow or PyTorch.
• Solid SQL for querying databases.
• Familiarity with ML Ops: MLflow, versioning, CI/CD for ML.
• Experience with data visualization tools (Power BI, Matplotlib, Seaborn, Plotly).

Responsibilities

• Design, build, and evaluate ML models for classification, regression, forecasting, and NLP use cases.
• Develop and maintain data pipelines using Python and Azure Data Factory / Databricks for ETL and feature engineering.
• Deploy ML models on Azure ML with endpoints, pipelines, and MLflow tracking.
• Collaborate with data engineers to ensure data quality and governance across Azure Data Lake and Synapse.
• Apply AI/GenAI capabilities to build intelligent apps and automation workflows.
• Monitor model performance in production; detect drift and retrain as needed.
• Translate business requirements into data science problem statements and communicate findings to stakeholders.
• Participate in code reviews, documentation, and ML Ops best practices.

Skills

Python

ML frameworks

Azure services

SQL

MLOps

Data Visualization

Git & Agile

Education

Bachelor's or Master's in CS/DS/Engineering/Math

Tools

Azure ML

Azure Databricks

Azure Data Factory

Azure Synapse

MLflow

Power BI

Git

Job description

About the Role

We are hiring a Junior 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.

Job Title

Junior Data Scientist

Employment Type

Full-Time

Experience

• 4-5 Years Experience

Department

Data Science & AI

Location

Hybrid / On-site

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 to 7 years of professional or project-based experience in data science or machine learning.
• Strong 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).
• Solid SQL skills for querying relational databases and analytical processing.
• Familiarity with MLOps practices: experiment tracking (MLflow), model versioning, and CI/CD for ML.
• Experience with data visualization tools (Power BI, Matplotlib, Seaborn, or Plotly).

Good to Have

• Microsoft Azure certifications: AZ-900, AI-900, DP-100 (Azure Data Scientist Associate) preferred.
• Experience with NLP libraries (Hugging Face, spaCy, NLTK) and LLM integrations (Azure OpenAI, LangChain).
• Knowledge of containerization and deployment: Docker, Kubernetes, or Azure Container Instances.
• Familiarity with big data tools: Apache Spark (PySpark) via Azure Databricks.
• Exposure to Generative AI, RAG (Retrieval-Augmented Generation), or Prompt Engineering.
• Version control using Git and experience with Agile/Scrum development methodology.

Technical Stack

Languages

Python, SQL

ML/AI Frameworks

scikit-learn, XGBoost, TensorFlow, PyTorch, Hugging Face

Cloud Platform

Microsoft Azure (Azure ML, Databricks, Data Factory, Synapse, OpenAI)

MLOps Tools

MLflow, Azure DevOps, GitHub Actions

Data & BI Tools

Power BI, Pandas, PySpark, Jupyter

Storage & DB

Azure Blob Storage, Azure Data Lake, SQL Server, Cosmos DB

What We Offer

• Competitive salary and performance-based incentives.
• Azure certification sponsorship and continuous learning budget.
• Mentorship from senior data scientists and ML architects.
• Exposure to cutting-edge AI/ML projects across domains.
• Flexible hybrid working model and collaborative culture.