Learning about BIG Careers (Business, Industry and Government)
- Read advice on Finding Nonacademic Jobs
- Join the Versatile PhD website and browse discussion boards there
- Visit Jobs on Toast
- Read the career transition stories at From PhD to Life
- Read SIAM articles on careers in the Mathematical Sciences
- Watch PICMath case studies on mathematics in science and industry
- Read How to Become a Data Scientist Before You Graduate and a blog post on data analytics in healthcare
Preparing for BIG Careers
- Visit your campus career office for an individual consultation
- Sign up on your campus jobs board: enter keywords and register for weekly updates
- Network with alumni from your program; ask the director of your graduate program for suggestions
- Tell mentors you are interested in industry and government careers, and see what connections and advice they have
- Decide on some career paths that interest you
- Develop skills – in-person
- Take courses and training workshops at your university on topics such as:
- regression, machine learning, data analysis and mining
- programming (e.g. Python, Matlab, Java, C++, object oriented programming, shell scripting), numerical methods, data structures
- stochastic processes, mathematical finance
- actuarial science, finance
- mathematical modeling
- Develop skills – online
- Take free courses are through Coursera, EdX, Udacity – search online for listings of courses on coding, algorithms, machine learning and data science
- Coursera now offers “specializations” and Udacity offers “nanodegrees”, for which students must pay in order to gain the credential.
- Prepare your résumé: see Résumé Advice and Samples from the University of Illinois (the sample résumés by Michaels and Russo show how to extract transferrable skills from your teaching experience) or see the Résumé Guide from the Science and Engineering Career Center from the University of Minnesota.
- Create a LinkedIn profile and upload a professional-looking photo. Include your email address in the profile, so that recruiters can easily contact you.
- Employers also like to examine a repository of your projects (if applicable). Github is perfect for that purpose.
Four Popular Career Choices
- Software engineering – advice from a Mathematics PhD graduate
- Finance industry
- A great book that talks about a physicist’s journey through becoming a quantitative analyst. My life as a quant
- Consulting industry:
- Many mathematicians find jobs in consulting firms, such as McKinsey, Boston Consulting Group, and Bain.
- Data science – intensive training courses. Check the reviews online (e.g. Glassdoor) before applying to these training courses.
Finding Jobs and Internships
- Register for your campus jobs board – upload your résumé to companies, view current postings for internships and jobs, get weekly digests of job postings matching your criteria, register for career fairs, sign up for on-campus company info sessions
- Check your university’s research park for opportunities (look for “careers” or “internship” links on their website)
- ASA Internships Board
- SIAM Job Board
- EIMS Job Board
- INFORMS Career Center – society for operations research
- National Security Agency
- National Labs
- Federal Government employment and the Presidential Management Fellows program
- MAA BIG SIGMAA.
See your campus career office for guidance on how to network effectively. Most job seekers do not find a job just by uploading résumés online – you need to make personal contacts!
More Links on Internships
- SIAM internship and career links
- Read about internship experiences of mathematics graduate students at the U of Illinois
- NSF Mathematical Sciences Graduate Internship Opportunity
Deadline was 8AM March 1, 2017
Preparing for Interviews – Technical Skills
- Software Engineering
- ProjectEuler.net has math/coding problems – you could form a group with other graduate students to tackle some of the problems!
- Hackerrank.com also has great problems to practice for coding interviews, on different topics such as algorithms, data structures, complexity, etc.
- Cracking the Coding Interview book
- Udacity Technical Interview Course (free)
- Data Science, Quantitative Analyst (for technology and finance)
In order to prepare for interviews, one needs to brush up skills in:
- Probability (sample questions)
- Basic Python
Preparing for Interviews – Soft Skills
- Michael Page – Top 5 soft skills to demonstrate in an interview
- 15 things not to do in an interview
- Public speaking