To whom it may concern,I want to make a career change, statistician working in biotech to quantitative finance, while holding a MS, MA and PhD in pure and applied math, masters equivalent and 5 years industry experience in statistics (using SAS, Stata and R), 3 years experience in the software industry (C/C++, Java, algorithms, distributive computing, data mining with Python, computational modeling and numerical analysis using MatLab). This past 1.5 years I spent studying PhD level probability and stochastic analysis along with basic concepts in finance. My math/stats over the course of graduate training included algebraic geometry, algebra, topology, geometry (including exposure to fractals), number theory, analysis (real, complex, Fourier and functional), PDE, dynamical systems (including non-linear oscillators and chaos), regression, generalized linear models, hierarchical modeling, Bayesian statistics, meta-analysis, categorical, survival and longitudinal data analysis. Physics during my undergraduate education included quantum mechanics (graduate level), statistical mechanics, electrodynamics and relativity. Basic academic finance familiarity included Hull's text and Bjork's Arbitrage theory in continuous time supplemented with lecture notes on derivative securities and stochastic calculus from NYU, When Genius Fails, Black Swan, Shreve's stochastic calculus for finance I and Baxter's financial calculus.Do you have any suggestions on a good job hunting strategy?Thank you for your time and considerationSincerely,Dean, USA

Quoteincluded algebraic geometry, algebra, topology, geometry (including exposure to fractals), number theory, analysis (real, complex, Fourier and functional), PDE, dynamical systems (including non-linear oscillators and chaos), regression, generalized linear models, hierarchical modeling, Bayesian statistics, meta-analysis, categorical, survival and longitudinal data analysis.That's a lot of topics.

A lot like 'a lot for someone to be good at'?@Dean: please clarify. You are just familiar with these subjects or you have more in-depth kknowledge?

QuoteOriginally posted by: dfeynmanA lot like 'a lot for someone to be good at'?Yes. A one-semester course does not count. To be honest, it comes across as a bit of bravado.

QuoteOriginally posted by: deancontentsTo whom it may concern,I want to make a career change, statistician working in biotech to quantitative finance, while holding a MS, MA and PhD in pure and applied math, masters equivalent and 5 years industry experience in statistics (using SAS, Stata and R), 3 years experience in the software industry (C/C++, Java, algorithms, distributive computing, data mining with Python, computational modeling and numerical analysis using MatLab). This past 1.5 years I spent studying PhD level probability and stochastic analysis along with basic concepts in finance. My math/stats over the course of graduate training included algebraic geometry, algebra, topology, geometry (including exposure to fractals), number theory, analysis (real, complex, Fourier and functional), PDE, dynamical systems (including non-linear oscillators and chaos), regression, generalized linear models, hierarchical modeling, Bayesian statistics, meta-analysis, categorical, survival and longitudinal data analysis. Physics during my undergraduate education included quantum mechanics (graduate level), statistical mechanics, electrodynamics and relativity. Basic academic finance familiarity included Hull's text and Bjork's Arbitrage theory in continuous time supplemented with lecture notes on derivative securities and stochastic calculus from NYU, When Genius Fails, Black Swan, Shreve's stochastic calculus for finance I and Baxter's financial calculus.Do you have any suggestions on a good job hunting strategy?Thank you for your time and considerationSincerely,Dean, USASince "regression, generalized linear models, hierarchical modeling, Bayesian statistics, meta-analysis, categorical, survival and longitudinal data analysis" is something you used in your statistics work, they should possibly open the list of your mathematical skills. I hope you're aiming at hedge funds and not some dull investment bank derivatives job which would stall your development (I don't think you can count on any financial upside either). Bishop's "Pattern Recognition and Machine Learning" is a good read before a HF job interview. I can send you more reading suggestions if it's indeed for a HF.

Thanks for your response. I agree, there is no way to be an expert in all fields.In short, is it better to exclude most the "abstract math" details from the CV except the degrees and job experience or cast a wider, more detailed net and let the hiring managers decide if various aspects of my statistical, mathematical and coding background and experience are transferable? I am trying to solicit insight on preparing a CV with verifiable experience. Longer version: The details about the coursework are too extensive to list and generally required one year minimum in most cases (2 masters and a PhD from different universities). I shifted from pure to applied math then statistics with computer science (including 3 years software industry experience) along the way. The statistics is based on nearly completing another MS degree and I have been working for the past 5 years as a full-time statistician in industry. I was required to gain familiarity with multiple branches of mathematics working on thesis problems and my dissertation, e.g., MS degree involved the classification of 2d-surfaces (topological problem) which historically was approached using Riemann surface theory, then harmonic analysis and ultimately solved using diffusion - Brownian motion on manifolds? My recent probability and stochastic processes training was part of a 1.5 year independent study program which followed the standard phd texts and extensive review of real and functional analysis (Durrett with Billingsley, Karatzas and Shreve with Oksendal supplemented with online course notes and masters level materials) with the intention of moving into quantitative finance.To clarify: Would presenting a more detail description of my math background help or hurt a CV for quantitative finance job hunting? My thinking is to try and present "transferable" skills so am requesting some guidance on what is transferable out of the list.RegardsDeanbtw: 1 grad course=40 hrs lecture+120 hours study+time required to pay tuition>160hrs=4 full time work weeks="does not count"? Please clarify this comment.

I was seriously considering targeting HF and started researching them. Any suggestions on the best approaches and process for HF job hunting? A book list would also be appreciated. At the same time, breaking into the industry is of highest priority, so must keep all options open.

Apologies, maybe I was a bit off-the-cuff. I was blinded by the long list of topics, any one of which takes years to be any good in. QuoteIn short, is it better to exclude most the "abstract math" details from the CV except the degrees and job experience or cast a wider, more detailed net and let the hiring managers decide if various aspects of my statistical, mathematical and coding background and experience are transferable?Pure maths is good to know but IMO it is not so useful in the current context. Maybe I am wrong. Applied maths, numerical analysis, stats and C++ skills are probably more important as you say. The issue with pure maths is that most of it cannot be put into algorithmic/constructive form. It is infinite-dimensional while algorithms tend to work in finite dimensions.Quote1 grad course=40 hrs lecture+120 hours study+time 120 hours is a start I suppose.

QuoteOriginally posted by: deancontentsAny suggestions on the best approaches and process for HF job hunting?Networking events and head hunters. Those are basically your only realistic options.

I have probably said similar things around here before, but if you can demonstrate that your (seemingly impressive) quant and research skills are real by writing a modest research paper of relevance to what you are trying to do, this would be a nice calling card. There would still be the question of how to get it in front of the right people, and for this Hansi is probably right; but having a piece of original research to show for you could be used as a tool to accelerate the networking process.

If anyone has professional advice on quant job hunting for someone with my background, it would be much appreciated.

QuoteOriginally posted by: katastrofaSince "regression, generalized linear models, hierarchical modeling, Bayesian statistics, meta-analysis, categorical, survival and longitudinal data analysis" is something you used in your statistics work, they should possibly open the list of your mathematical skills. I hope you're aiming at hedge funds and not some dull investment bank derivatives job which would stall your development (I don't think you can count on any financial upside either). Bishop's "Pattern Recognition and Machine Learning" is a good read before a HF job interview. I can send you more reading suggestions if it's indeed for a HF.Why do you say derivatives jobs are dull? Why would they stall one's development?