Key Qualifications
Experience:
1–2 years of software development experience (preferred)
1–2 years of experience as a Data Scientist, with a focus on Time Series forecasting
4+ years working with Azure Cloud platforms, including:
Azure Databricks
Azure ML Studio
Azure Data Factory (ADF) Pipelines
Technical Skills:
ML Ops / DevOps practices and tooling
CI/CD pipeline configuration and deployment
MLFlow for experiment tracking and model management
Strong programming skills in Python
Experience with machine learning models such as:
Random Forest
XGBoost
LightGBM
Other ensemble modeling algorithms
Education:
Bachelor's or Master's degree in Software Engineering, Computer Science, Statistics, or a related field
PhD not required
Soft Skills:
Rapid learner with the ability to adapt to changing priorities
Strong problem-solving and collaboration skills

Role Responsibilities
Function as a developer with a strong focus on:
ML model implementation, experimentation, and deployment




Applying software engineering best practices in machine learning projects
Conduct data analysis and work with forecasting algorithms, especially for time series data
Collaborate with cross-functional teams to deliver production-level ML solutions

Tools & Technologies
Azure Databricks
Azure ML Studio
Azure Data Factory (ADF)
MLFlow
CI/CD tools (e.g., GitHub Actions, Azure DevOps, Jenkins)
Python and relevant ML libraries (e.g., scikit-learn, pandas, numpy, etc.)

What We Offer
Opportunity to work on cutting-edge ML projects
A highly motivated and collaborative team
Market-competitive salary
Flexible schedule
Benefits package including:
Medical insurance
Sports membership or wellness stipend
Corporate social events
Professional development opportunities
Contemporary, well-equipped office environment

📌 Senior Data Scientist Secunderabad
🏢 Grid Dynamics
📍 Secunderabad