The Data Scientist / Analytics Consultant designs and delivers data analytics and machine learning solutions that support business decision‑making. This role translates business problems into data‑driven models and insights, contributes to client engagements, and supports solution design using cloud-native analytics, ML, and emerging GenAI capabilities across Microsoft Azure, AWS, and Google Cloud platforms.

Design and deliver analytics and machine learning solutions aligned to business problems and client objectives

Perform advanced exploratory data analysis (EDA), feature engineering, and data modeling

Build, evaluate, optimize, and validate machine learning models

Develop and maintain data pipelines, transformations, and model workflows

Create insight-driven dashboards, reports, and analytical narratives for stakeholders

Support solution design discussions, estimations, and technical documentation

Collaborate with clients, business stakeholders, and delivery teams

Ensure adherence to data governance, security, quality, and compliance standards

Leverage cloud AI and GenAI tools responsibly to enhance analytics delivery

Skills

Robust analytical, statistical, and problem‑solving skills

Hands-on applied machine learning experience

Ability to translate business requirements into analytics solutions





Experience in client-facing communication and stakeholder management

Understanding of data governance, quality controls, and model validation

- Structured documentation and presentation skills

Tools and technologies

Microsoft Azure

Azure Machine Learning (training, experimentation, deployment)

Azure Data Factory / Azure Synapse / Microsoft Fabric (as applicable)

Azure SQL Database, Azure Data Lake

Power BI (semantic models, dashboards, optimization)

AWS

Amazon S3, AWS Glue (data ingestion & transformation)

AWS SageMaker (model development and experimentation – working knowledge)

Google Cloud (GCP)

BigQuery (analytics – working knowledge)

Vertex AI (model experimentation – exposure preferred)

Programming & Analytics

Python (scikit‑learn, pandas, numpy, statsmodels)

SQL

GenAI & AI Platforms

Azure OpenAI / Microsoft Copilot (analytics augmentation, summarization, insight generation)

Google Gemini (awareness / experimentation)

Anthropic Claude (assisted analytics, documentation, analysis use cases)

DevOps & Collaboration

Git (version control)

Azure DevOps (CI/CD pipelines, work item management)

Certifications Needed

Microsoft Certified: Azure Data Scientist Associate (DP‑100)

Or

AWS Certified Cloud Practitioner

Or

Google Cloud Digital Leader

📌 INDUS Consultant - Data (Bengaluru)
🏢 Grant Thornton INDUS
📍 Bengaluru