Jane Street’s Post

Continuing the previous post (part 3) One of the recipe of success of Jim Simons's was EMPLOYEE HIGH IQ DOCTORS NOT INVESTORS: Jim Simons wanted a team with high IQ levels who could solve the complex mathematical equations easily and can help him earn greater returns. So, instead of hiring investors he himself went to universities and hire people who had doctorate degree in maths, physics, astronomer and statisticians. Simons said that: The important thing is that they were very smart and he can teach a physicist finance but not a finance person physics. One more thing Simons did was: He didn't hired these peoples aa employees but instead hired them as partners. (PS- no harm to financers and investors).

People who study #appliedmathematics “get shuffled into the traditional outlets… like math academia, finance, computer science, data science… and as a result they almost certainly have an over-allocation of #talent.” 🤔 I've always looked at the employment market in terms of where my talent is demanded, but taking that perspective is only equivalent to looking at it in terms of where my talent is under-allocated if the labor market is efficiently allocating talent according to relative levels of demand. It's an interesting way to think about career planning but it faces you with convincing a skeptical employer that you understand their needs better than they themselves can articulate them. (This is one proof you can't leave to the reader.)

For the "To Read" shelf: Skrentny provides a quick summary in this TV interview, at least implicitly making the case for educating as much as possible before one trains for specific work, and for the importance of cultivating broad literacies to be able to navigate a constantly changing, tech-driven work world. He notes that companies tend to be more interested in buying talent than building it from within, and that workers get exhausted on the reskilling treadmill. #futureofwork #multipleliteracies #education #reskilling https://lnkd.in/gV_f_Ydm

Excited to share my article on 'Beyond Words and Algorithms', titled 'Why a Ph.D.?'! In this post, I put forward my journey toward starting a new Ph.D. and all the decisions and contemplation that came with it. 😁 It is a small and, hopefully, fun read that a lot of people can relate to! Please do share your thoughts. I will also be very happy to receive some Ph.D. advice from all the research veterans here! If you're interested in this, please explore the blog for more such articles on the work we do and our (Sanjana Gautam, Pranav Venkit, Mukund Srinath) respective journeys. https://lnkd.in/eNBVtndA

I am thinking that the future will demand visionaries who not only cross disciplinary boundaries but also redefine them, paving the way for innovative solutions to problems that remain unidentified due to our existing limitations. 👩🦰What do you think? Annie --- A colleague once lamented about a controversy in their academic department (computer science) involving a potential new hire. The candidate in question was formally trained in physics but had a strong record studying information theory, which was of interest to the department. I asked what the fuss was about, to which the colleague replied: “Some folks don’t think physicists should be in a computer science department.” The candidate wasn’t offered the job. There are many problems with these sorts of dustups. In this specific case, the biggest crime is the overreliance on an umbrella category (“physicist”) to mark someone’s appropriateness for a job. The departmental protest was not about the candidate’s skill set or accomplishments, but simply about the nominal category-fields through which they were trained. ...READ More... #FutureOfWork #DiverseSkillset #InclusiveWorkplace #SkillsForSuccess Hon.

Download free activities, incorporating components from ALEKS, to help make your Pi Day celebration engaging and fun for students! 🍕 #Math #Mathematics #PiDay

This graph shows what many of you have experienced throughout your careers, doesn't it? I mean you KNEW this, at least at some level, right? But did you KNOW this, in hard numbers? Wow. Productivity increase: 64.6% vs. Compensation: 16.3% (1979 - 2021) (it's from Robert Reich's UC Berkeley class on Wealth & Poverty, he posted all 14 lectures for free on You Tube). This is the first class (I like to listen/watch while I clean or cook - how about you?) I'll be sure to watch the classes on"Globilization, Tech, and the Future of Work" and "Monopoly, Labor & Antitrust" though hope to see them all. Link if you're interested: https://lnkd.in/efcQGhvY

An exciting start to the week! our paper "Large Language Models for Qualitative Research in Software Engineering: Exploring Opportunities and Challenges" has been accepted by the 'Automated Software Engineering Journal - Future Track'! This collaborative effort with my amazing co-authors Rashina Hoda, Prof Didar Zowghi, and Christoph Treude explores the integration of Large Language Models into qualitative research within software engineering, addressing both potential benefits and challenges. Read more about our findings and the future directions we propose in this field by visiting the link below.

Your article reached 20 citations Well done! Nikolaos's article reached 20 citations Achieved on July 27, 2023 Article: Towards Smart Energy Grids: A Box-Constrained Nonlinear Underdetermined Model for Power System Observability Using Recursive Quadratic Programming

Does analytical science have a #reputation problem? Lucas Sternbauer discusses the possible origins of the field's misconception as a "push-button job" in our #ReadoftheWeek and explains why education is the most powerful tool that can elevate the profile of analytical science... Read the full article here> https://bit.ly/4byJCPQ