Careers outside Academia - USC Computer Science Masters and Ph.D. Students

750 views

Published on

Talk given at USC CS Colloquium to grad students (http://viterbi.usc.edu/news/events/?event=10265). The topic was - Prospective Careers outside Academia.

Published in: Education, Technology, Business
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
750
On SlideShare
0
From Embeds
0
Number of Embeds
6
Actions
Shares
0
Downloads
5
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

Careers outside Academia - USC Computer Science Masters and Ph.D. Students

  1. 1. First steps to a Successful Career Ashwin Rao USC, Los Angeles, Nov 2013
  2. 2. My background •  B.Tech. Computer Science. IIT-Bombay. •  Ph.D. Algorithmic Algebra. USC, Los Angeles. •  VP. Quant Strategist. Goldman Sachs, NY. •  Managing Director. Morgan Stanley. •  Founder. ZLemma.com (A Tech Startup)
  3. 3. Life after ‘SC •  USC tag follows you J •  Learning curve actually gets steeper •  Acquire versatility in skills and personality •  Associate with people different than you
  4. 4. What are suitable jobs for me ? •  You can figure it out objectively •  Glamour, Money and the Mom Syndrome •  Introspect on your Skills and your Interests •  Think Career, not Jobs
  5. 5. Prepare Well, but Chill Out •  Research the various jobs thoroughly •  Advice from peers and alumni? •  Personal Life versus Professional Life •  Never compare yourself with others! •  Easy to correct bad jobs or wrong decisions
  6. 6. Should I go to Grad School? •  Titles like M.B.A., Ph.D. - what is their value? •  What do the best employers care about ? •  Ph.D. è If you want to be in academia/research •  M.B.A. è If you want to hit the Reset button •  Masters versus Ph.D.
  7. 7. Quant Finance Jobs •  Derivatives Trader •  Trading Desk Quant Strategist •  Derivatives Modeler, Statistical Modeler •  Algorithmic Trading Quant •  Analytics Developer
  8. 8. Current Wall Street Scenario •  Regulations have reshaped the industry •  Compensation levels down but still high •  Engineers are thriving in quant finance •  Markets turning increasingly electronic •  More emphasis on vanilla trading businesses
  9. 9. Tech Jobs •  Boom in Tech, particularly in Silicon Valley •  Compensation levels are growing fast •  Big Data is the new buzz •  Google, Facebook, Apple, Amazon •  Are Tech jobs boring?
  10. 10. Silicon Valley versus Wall Street •  Do you enjoy Continuous Math? •  Depth versus Breadth •  Office environment and Colleagues •  Compensation •  Location
  11. 11. Some important topics •  Statistical Learning •  Functional Programming •  Domain Specific Languages •  Quantitative Modeling •  Architectures for Big Data
  12. 12. Startups •  Appetite for Volatility •  <Market, Product, Team> •  Funding •  Advisors •  Passion
  13. 13. Resume •  One-pager with precise education/work details •  Links to LinkedIn, Github, Stackoverflow … •  Reflection of your communication skills/style •  Less drama, more objectivity •  State your international exposure, if any
  14. 14. Interviews •  Represent your abilities clearly and accurately •  Typically, a large and diverse set of interviewers •  Flood of puzzles/programming/math problems •  Tough Qs in your claimed areas of expertise •  Evaluation of your communication and attitude
  15. 15. ZLemma •  Zlemma.com evaluates your profile in great detail •  Zlemma Quotient (ZQ) – your suitability for a job •  ZQ is a score out of 100 for a specific job •  Apply for high-ZQ jobs of interest to you •  Jobs ranging from Silicon Valley to Wall Street
  16. 16. Addendum •  Tune in to: blog.zlemma.com •  Write to: ashwin@zlemma.com for advice •  Our app is your friend: zlemma.com

×