Associate Software Engineer - 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.

• 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.