How is the financial data analytics program from IIM Kashipur?

The Financial Data Analytics Program is designed for working professionals from the Financial Modelling domain. This course develops an understanding of advanced techniques that can help them solve financial problems in a simpler way. The elements related to Financial

Modeling enlighten the students about financial

statement analysis, risk-return Modeling, and basic portfolio analysis among many others. Some core features of this course are

• The program comprises 6 terms (3 terms in the first year and 3 terms in the second year).
• Various corporate organizational issues and decisions are taken care of by MBA Analytics professionals.
• The curriculum is a healthy blend of academics, extracurricular activities and industry exposure
• The course offers a learning environment to tackle the increasing demand for complex data analysis.

Career Opportunities:

• IT System Analyst
• Healthcare Data Analyst
• Operations Analyst
• Data Scientist
• Data Engineer 
• Quantitative Analyst
• Data Analytics Consultant

MBA Analytics fees: 

Placements: 

IIM Kashipur maintains a good placement record every year. The final placement report for the MBA batch of 2022 has been released.

Highest Salary: INR 28.82 LPA 

Average Salary: INR 15.21 LPA

Median CTC - INR 14.82 LPA

Number of students: 322

A total of 365 offers were made and more than 150 companies visited the campus during IIM Kashipur MBA placements 2022. Also, the institute witnessed an increase of 47% in PPOs/PPIs along with a 26.6% increase in the number of recruiters.

During the placement drive, the highest number of offers came from the IT & Analytics sector. 39% of the offers came from the IT & Analytics sector, 30% of the offers came from the BFSI sector, and 11% of the offers came from the Management Consulting sector. Less than 10% of the total offers came from E-Business, Retail, Manufacturing & other sectors. Some reputed firms that visited the campus for placements are Virtusa, Flipkart, HP, Loreal, Accenture, Deloitte, EY, Dell, Cognizant