Gartner Expert

Farhan Choudhary

Assoc Principal Analyst

Farhan Choudhary is a part of Research Analyst Lab focusing on Artificial Intelligence along with Data Science, Machine Learning and Deep Learning. He helps clients with best practices around operationalizing machine learning models, hiring and upskilling, organizational strategies, platforms/tools (buy vs. build vs. outsource) - finding the right platform/tool, pricing and contract reviews, and productionization techniques (DataOps, MLOps, ModelOps) to operationalize and achieve success with data science, ML and AI initiatives. He co-led the Gartner Use Case Prism Framework and with that guides organizations on the strategic, organizational and technology aspects of using advanced analytics as a driving force of their growth.

Previous experience

Mr. Choudhary previously worked in the area of air quality monitoring using IoT sensors and lead the first low-cost sensing network in New Delhi, India. He used the resulting data for analysis and air quality forecasts.

Previously, Mr. Choudhary also worked as a Data Scientist for various government, law enforcement, banking, financial services and insurance (BFSI) and private agencies in India and overseas with projects in financial data analytics, natural language processing and deep learning with computer vision (video/image analytics).

Professional background

Kaiterra

Technical Manager

IL&FS Technologies Limited

Data Scientist

EY

Analyst

Areas of coverage

Analytics, BI and Data Science Solutions

Data and Analytics Strategies

Artificial Intelligence

Education

M.B.A., Dual Major: Finance and Marketing

Bachelor of Technology, Electrical Engineering, Additional Specializations in Data Science and Deep Learning

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Top Issues That I Help Clients Address

1Using AI, data science and machine learning to achieve competitive differentiation

2How to create a nurturing AI-centric organizational culture and aligning resources to various functions

3How to start your data science, machine learning or AI journey using different tools and platforms and shortlisting use cases

4Navigate data science machine learning vendor landscape, and contract/pricing reviews.

5How to operationalize AI/ML models and be future ready