Johnson Controls is hiring fresher’s and experienced candidates for the role of Associate Software Engineer – Data Scientist. The complete details about role are as follows.
Johnson Controls Hiring | Associate Software Engineer – Data Scientist
Company : Johnson Controls
Role : Associate Software Engineer – Data Scientist
Degree : Graduate, B.Tech/M.Tech
Batches : Any Batch
Experience : 0 – 5 Year’s
Salary : 3 – 25 LPA (Expected)
Location: Pune, India
Job Description:
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.
Qualifications & Skills :
- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Mathematics, or related field.
- 0–2 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.
Roles and 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.
How To Apply For Johnson Controls Careers :
- Click on the “Apply Here” button provided below. You will be redirected to Company official career page.
- Click on “Apply Online”.
- If you have not registered before, create an account.
- After registration, login and fill in the application form with all the necessary details.
- Submit all relevant documents, if requested (e.g. resume, mark sheet, ID proof).
- Provide accurate information in your application.
- Verify that all the details entered are correct.
- Submit the application form after verification.
Johnson Controls Apply Link: Click Here
Telegram Group : Click here
Join our WhatsApp Group: Click here
All Jobs : Click here
About Johnson Controls :
Johnson Controls is a global technology leader in energy efficiency, decarbonization, thermal management and mission-critical performance.