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Maybe while they are at it they can make some additional $$ improving NYC MTAs sensor network so MTA can know where the trains are!

Context: I am a data analyst who previously was an auditor. JIRA was a game changer for me and I would have loved to have used it during my Audit career. As such, I want an Issue Tracker that works for technical and non-technical individuals.

I would want my Issue tracker to be deeply integrated with the company's Shared File System and Developer tools so all team members have a place to share their work. The Task page would be a place where all the work done could be shared in a clean way and even serve as a quasi-wiki. Like a Jupyter Notebook, I would love to include Markdown and Code along with attachments, analyses, and opinions. Everything would be included, not just the final relevant pieces. Side-analyses stemming from anomalies and potential issues would be hidden but there for those who need them. If something changed in an attachment like an Excel file, these changes would be reflected. Adding dependencies on files and the information contained within them could be linked so that if Account Manager A changes File B, I know that my work on Ticker 123 is now potentially conflicted.

Some finance books I love (and reread frequently). These books are more about characters and stories, more than traditional non-fiction.

My Life as a Quant by Emanuel Derman

The Quants by Scott Patterson

A Man for All Markets by Edward O. Thorp

Reminiscences of a Stock Operator by Edwin Lefevre

Flash Boys by Michael Lewis

> "not the need to find my place in life at this stage,"

I appreciated this perspective. My primary motivation for pursuing deep work is due to an insecurity with my current ability to be useful to the economy. If this was validated or I solved the mental part of it, I suspect the anxiety would lessen a bit.

I like to think of myself as having "alternative" priorities :) Thanks a bunch!

I think a key factor in this decision may be the perceived risk of putting huge capital behind a single black box model. I would assume this differs from more ML-heavy quant firms like Two-Sigma, because BlackRock's products generally perform at a huge scale with some central idea behind them. Two-Sigma probably can spread out the same amount of assets across many different black-box models, diversifying and reducing risk through these means. In this case, perhaps only 1 model dictating such a huge chunk of capital was just too much uncertainty?

I have no evidence of the scale and diversification of both these, so evidence would be helpful in refuting the above!

Business Intelligence Roadmap by Moss and Atre

Some crazy stat exists related to this. Something like Apple making less than 15% of global units while reaping some 80% of the global profits related to said units. In this case, I weigh profits as the best manifestation of the company's position and not units produced.

Software engineering (not as a job) for data analytics and data science that help me automate information consumption.

A clock face is a timeless UI

My friends think its passion, but really I just forced the medicine down until it became habit, then a permanent fixture, and now is familiar and relaxing. I love learning new things but the "passion" idea is really just me exploring the nuanced depths of a topic I now know a lot about, and that seems to be fulfilling enough that it can masquerade as "passion" to outsiders.

They aren't all self help. Some just shook my world view so much that I couldn't help but introspect, reviewing everything I believe from a new angle. I find the experience I had with each fairly intimate. I hope others may have the same experience with any book, but think that these may do it.

1. This Is What I Talk About When I Talk About Running - Haruki Murakami

Murakami talking about his decision to become an author and also his lifelong hobby of running.

2. Let's Explore Diabetes with Owls - David Sedaris

Made me laugh for the first time in awhile.

3. The Myth of Sisyphus - Albert Camus

Absurdity.

I would like to give my 2 cents on where I see any opportunity!

A newer quant will be incentivized to create an equity strategy because the data is available and the markets are liquid. Because the equity markets have been automated for so long, a lot of the inefficiencies and arbitrage opportunities have been leveraged. If a user were to come across an opportunity, it would most likely disappear quickly, which then can lead to your strategy hemorrhaging capital.

An alternative would be to secure data feeds and invest time in less heavily traded securities, trading liquidity for reduced competition. This becomes a much scarier idea, because you may not be able to exit your positions if they slide away from you. It would generally be hard to get the right to trade these securities without large amounts of capital or a big name behind you, but this is part of your advantage.

An omnipresent underlying sense of anxiety and rage caused by something or other in my past that is useful for work but not useful for building relationships!

I heard an iOS developer make a comment once saying that deciding to develop for iOS means less folks may have access (under the assumption that Android is more common) but you are guaranteeing that those with access to your application have more money to spend because of Apple's price point. If Facebook's targeting and ad exchanges are what productize the company's customers then I would say Apple does the same to a lesser degree by charging a premium for its exclusive ecosystem. I consider Apple many degrees safer because they heavily screen what can be added to the app store and the inherent nature of targeting going on is limited to "paid for an Apple device" instead of the greatly higher dimensional data accessed leveraged by Facebook.

Folks hate on Upwork.com but I have used it to secure and build good long-term relationships. Once the relationships grew we could take it offline to a more formal relationship. Because I started my career as an accountant, I have been able to start 2 of these relationships as an accountant and move over to data analysis.

A good note to include is I do this part-time while working full-time and don't think I could simply expand this contract deal flow to fill a full time schedule if I needed to. I also have ruined a relationship early on by not respecting the part-time work enough and slowing down the folk's timeline.

A semester during my undergraduate degree, my registrar account was allowed to sign up for a class after I made a case they should waive the pre-requisite for me. During my sign-up window, I was unable to enroll in the class before it was filled, but noticed I could sign up for any class without being flagged. I ended up taking the most difficult classes in my program all at once, forcing myself to work near 24/7, riding the wave of volatility with heavy consumption of substances. The final result was a firey explosion, but at least it happened the next semester and I was able to graduate early while mostly taking electives for my last semester.

This period of "productivity" taught me a lot. As a lot of folks here are already aware, it is a slow and difficult process to increase the workload one can handle. Temporary support from things like caffeine, sugar, alcohol or drugs can extend these periods making it easy, but over time the effect weakens as you become more familiar with the mental state, making the initial support a crutch. Years later when completing my masters, I found the urge to fall back on some of the habits incredibly appealing during the weeks when I felt stressed and wanted to go on "autopilot". If I look at the future productivity earned from the compound interest of staying up, angry and upset, but still working through the discomfort, then I have had nights that were 10x what that semester in college was, because those nights will yield 100s of hours in the future that I would otherwise not be able to work through.

The big pieces that have helped me understand and grow with tf:

I began learning a lot about the workflow through cookbooks with dialogue on why specific practices are used. My favorites started small with something like a linear regression model and hit all the major notes up to neural nets. If you go this route, I would pick something published recently so you are starting with the current version and can learn the new features as they are released.

From there I could begin to understand online tutorials on implementing this or that model. This gave me a lot of context on how I could begin testing different ideas and tuning my hyper parameters in my own models.

Someone who is a true pro can take if from here.

Like Midas, it is the dream of all green auditors until they find it and realize the downsides.

I applied it to a sizable chunk of company expense data when auditing accounts payable. It highlighted some managers who made consistent purchases from the same vendor, not the multi-million dollar fraud I was hoping to find.