Azure Data Scientist

1w1 week ago

UNIFY Dots

Pune, IN · Full-time · INR 1,500,000 – INR 2,500,000

About this role

UNIFY Dots is a global technology and software solutions company specializing in Microsoft Dynamics 365 based solutions. The Azure Data Scientist will design, build, and experiment with machine learning models using Microsoft Azure. This role translates business goals into machine learning problems and success metrics.

Day-to-day involves designing and implementing data models for analytical and machine learning workloads. Perform feature engineering and selection based on business context. Build, train, evaluate, and iterate machine learning models while running experiments in Azure Machine Learning.

Use notebooks for data exploration, model development, and validation. Document assumptions, model behavior, and results for business and technical stakeholders. Collaborate with data engineers and solution architects to ensure data readiness.

Work closely with business and technology teams to align models with real business outcomes. Gain exposure to ML lifecycle practices including experimentation, evaluation, and deployment readiness. Thrive in cross-functional teams focused on Microsoft Azure technologies.

Requirements

Bachelor’s Degree in Computer Science, Engineering, Information Technology, or related field
3–5 years of experience in data science, machine learning, or related roles
Strong experience with Python for data analysis and machine learning
Experience with Azure ML Python SDK (v2)
Hands-on experience with Azure Machine Learning (workspaces, experiments, models)
Proficiency using Jupyter Notebooks in Azure ML Studio for experimentation and modeling
Solid understanding of data modeling concepts (features, labels, training data, validation)
Certified in Microsoft Azure AI Fundamentals (AI-900) and Microsoft Azure Data Fundamentals (DP-900)

Responsibilities

Define business goals and translate them into machine learning problems and success metrics
Design and implement data models suited for analytical and machine learning workloads
Perform feature engineering and feature selection based on business context
Build, train, evaluate, and iterate machine learning models
Run experiments and track results using Azure Machine Learning
Use notebooks for data exploration, model development, and validation
Document assumptions, model behavior, and results for business and technical stakeholders
Collaborate with data engineers and solution architects to ensure data readiness