Not the typical finance path but I think it can be relevant here in thePEforum and a unique example of how a career can progress. Still figuring out what I would like to do in the very long term, but the near term is looking good so far! Ask away here or feel free to PM me ...
Background:
-heavy math/science interest from a young age
-done obtaining certifications and currently diving into quantitative finance andtradingadvanced options in my free time
-Accounting (business school) and Data Science (engineering school) majors at a top 50 US university located in TX
-first job out of undergrad at Big4 had me doing big data projects for mega-cap corps
-at same Big4, I moved into a technical accounting group working on live deals (SPACs,IPOs, traditional M&A)
-before promotion at Big4 I jumped ship to an EnergyPE/AMfirm in TX where my role can be best described as corporate development strategy & special projects with line of sight/exposure to the founders and avariety of front office功能
Comments (8)
Thank you for doing this,how does your work differ from someone who did 2 years of banking and then came in, how's the career trajectory that you have at you're current firm,did you develop an interest inPEafter working or you've had it from before,why not banking/consulting after undergrad,feel free to not answer any or all of the questions above, and congratulations! it's amazing what you've achieved.
I think these can be answered in three distinct parts:
Difference - someone doingIBfor two years out of school would have a leg up on industry knowledge and general sell-side deal proficiency. My work in Big4 spanned multiple industries and focused on the financial reporting and technical accounting issues (ex: embedded derivatives in warrants in a SPAC deal). For me, this experience has led me to currently seeing projects that get into the weeds of fundamental business inputs for financial services, which can get quite intangible.
Trajectory - very much up in the air but I wanted to take this chance leaving the structured ascent of Big4. I could climb the corp dev side given successful growth in the business or with internal connections move to a buy-side/IBarm of the firm.
Interest - the big data work was fun butreally back officeon the decision-making side. I followed the action to the deals group. Worked on a fewPEPortco projects (which IPO'd and SPAC'd) and found locally the kind of firm I had on the client side to go work for.
What do you think is your trajectory, and can you talk more about the projects that you work on?
Trajectory- see answer to another question, but to specify it would be CFO/COO or Operating Partner with a transferable skill set across firms like mine and operators in the energy industry. Not counting out going over to the dark side though (buy side)
Projects- without giving too much away, my projects revolve around two focuses: 1) process and 2) forecast. I'll lay out some of the questions I'm tasked with answering. The fun part is these are generally open-ended.
1) Process: what are the blind spots in our current process coverage? Where can this be more efficient? What business lines need to be linked/included in communication?
2) Forecast: given an investor scenario, what do these cash flows look like (can go down thisPErabbit hole)? Where on the calendar are we weak in the cash cycle for next year (can we reinvest in the business consistently)?
Thanks for doing this! I'm a fellowCPAwho transitioned into data (currently in analytics consulting at the Big 4). My questions are:
1.什么数据工具/语言(例如PowerBI, SQL, Python, Alteryx, etc.) are you using in thePEside for your data work? I'm interested in getting into aPEPortfolio role of some sorts that combines finance/data and am curious what skills they're looking for. From my limited time in data (made the transition fromCPAto analytics about 4 months ago), I taught myself Python but have personally found it to be pretty overkill because there's a lot of no-code stuff that can do the ETL portion and most of the stats is relatively basic. This, however, is mostly on the business analytics side, where companies are less sophisticated or have less of a need for crazy quant stuff for most business questions. I'm curious if this is true inPEas well
2.什么类型的过程你都涉及工作d with on the finance side and where do you see these needs evolving from a data perspective? Long story short, I personally think there's a ton of opportunity for people who are both data and business savvy going forward because a lot of the corp fin "Modeling" finance professionals do is fairly rudimentary. That coupled with the fact that there's so much data to be extracted that can help with decision-making makes me think someone who is proficient enough to work with large datasets and can understand business needs/sift through a lot of noise (i.e. more data isn't always better) would be extremely valuable down the road. I'm curious if you feel the same.
Thanks again!
Generally, and I think this will answer both of your questions, I am not using any crazy data tools. We do have folks on the investments teams using energy industry-specific platforms and there are many great data points to grab and implement to something like Alteryx to get to an A or B or Do Nothing business decision. Because my work requires some out-of-the-box thinking and connecting rather disjointed "data points" I do benefit from my time spent programming in SQL and studying topics like linear algebra. Being able to ID key data points through the noise is where I am driving value in our processes. Most importantly above any one platform to solve data needs is having interdepartmental communication and mutual understanding of responsibilities. After that you can bolt on any enterprise software solution and scale up that efficiency.
你会如何过渡a big 4 intern toIBDatBB/EB/PE/MBB? Thanks
Rerum temporibus eos in nemo. Aut recusandae saepe eum fugiat beatae. Quas molestiae doloremque facere laborum aut ut. Corrupti velit omnis voluptas.
Quam eum vitae voluptatibus eos molestiae. Eligendi recusandae maiores neque quis sint et ipsum. Sed ratione dolor sed laborum.
Numquam aut hic sit sed est. Aliquid unde pariatur alias.
Vitae illo explicabo quia molestiae qui quasi. Ullam consequatur dolor ipsam. Ipsa quam aspernatur molestias architecto similique dolorum neque non. Labore velit et est dolores aperiam quia minima in.
See All Comments - 100% Free
WSO depends on everyone being able to pitch in when they know something. Unlock with your email and get bonus:6 financial modeling lessons free($199 value)
orWant toUnlockby signing in with your social account?
Preview & download comment as image
You can download this screenshot as image or copy to clipboard using browser's context menu