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Non-finance jobs for MFE graduates

Joined
5/2/06
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This was asked more than a few times on Quantnet but there was not a definite answer. Here is an attempt to collect all the alternative career choices for MFE graduates in non-financial companies.
http://www.linkedin.com/jobs?viewJob=&jobId=2093999&trk=rj_em&ut=1uZijUMrwZTAY1
Quantitative Analyst- Social Game Start-up

Job Description
Rocket Ninja, an innovative, well-funded start-up, seeks a talented Analyst to develop and implement quantitative, data-driven metrics and analysis for cutting edge social network games. The Quantitative Analyst is a key member of our creative, collaborative team, driving monetization and game design. He/she will build databases, design analytical models, automate data extraction and aggregation, implement data models in Excel, and be responsible for providing the data and analysis to support the company’s initiatives. The Analyst will work closely with Engineering to design and obtain data from existing databases using MySQL and other tools.

Desired Skills & Experience

Major Responsibilities:
  • Integrate multiple data sources with third party analytic applications.
  • Develop robust custom queries to assess data.
  • Build robust Excel models.
  • Collaborate with the VP Finance & Analytics and the technical team.
  • Recommend and implement approaches for efficient data processing.
  • Work in a fast-paced environment.
Requirements:

  • 3+ years professional experience writing customer SQL queries and designing SQL databases.
  • Bachelors degree in a quantitative discipline (Engineering, Mathematics, Statistics, Economics).
  • Familiarity with Google and Facebook analytics a plus.
  • Advanced Degree in Engineering, Mathematics, Economics, or Financial Engineering a plus.
  • Skill with MySql, Oracle or similar RDB’s required.
  • Advanced Excel skills and/or experience working with Visual Basic a huge plus.
  • Experience automating reports, data aggregation and data analysis required.
  • Experience integrating with reporting middleware.
  • Knowledge of data clustering, user segmentation, and statistics a plus.
  • Familiarity with Google and Facebook analytics a plus
  • Experience with live, online A/B testing desired
  • Initiative, resourcefulness, flexibility and start-up experience required, preferably in games or e-commerce.
  • Your interest in social games makes it fun, and a sense of humor will keep it all in perspective.
 
I agree that it's wise to make sure you have somewhere to run if Plan A goes belly up.
 
Hmm, well in this day and age, I throw my resume anywhere I can visibly see myself working. Don't qualify for the first opportunity though (more exp is required!)
 
http://www.linkedin.com/jobs?viewJob=&jobId=2293075&goback=.nmp_*1_*1_*1_*1_*1_*1&trk=rj_nus
Quantitative Analyst - New Grad
Twitter - San Francisco (San Francisco Bay Area)

Job Description
We’re looking for highly motivated individuals to help us extract meaning from Twitter’s massive dataset. As a Quantitative Analyst, you’ll use statistical analysis and data mining techniques to help us better understand how users engage with Twitter, determine whether new and experimental features should be launched, and measure Twitter’s success across the entire organization. You should be passionate about finding insights in data and using quantitative analysis to answer complex questions.

Responsibilities
  • Work with large (terabytes of data, billions of daily transactions) structured and unstructured data sets.
  • Work closely and iterate quickly with product teams throughout the organization.
  • Summarize and report analytical findings in both oral and written form.
  • Write and interpret map-reduce style data analyses using Hadoop and Pig.
  • Code using a mix of SQL, Pig, R, and scripting languages.
Requirements
  • MS or PhD in Statistics, Math, Operations Research, Computer Science, or another quantitative discipline
  • Experience with statistical programming environments like R
  • Experience with scripting languages, regular expressions, etc.
  • Interest in working with large datasets and map-reduce architectures like Hadoop
  • Interest in using discrete math, probability, and statistics to answer complex questions
 
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