Junior Data Scientist
Full-Time · 4-5 Years Experience
Department
Data Science & AI
Location
Hybrid / On-site
Experience
4-5 Years
Employment Type
Full-Time
Notice Period
Immediate Joiners Preferred
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.
- 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.
- 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).
- 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.
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
- 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.
