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A Day in the Life: Analyst in a Quantitative Analytics Group (Energy)

Published: Jun 01, 2021

 Day in the Life       
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7:30 AM: Arrive at the office at your usual time – work hours are more or less similar to those of the traders, mirroring the operating hours of commodities exchanges.

7:30 AM: Arrive at the office at your usual time – work hours are more or less similar to those of the traders, mirroring the operating hours of commodities exchanges. Overnight, you left a position report program running on the server, and now you start the day by reviewing the consolidated results that were automatically dumped into a directory on the office network. To your relief, there are no errors. (Yesterday you spent all morning working with IT to trace the source of an error to a corrupt file in the trading floor system, and then reprocessing the whole desk.) So, you create the daily VaR (Value at Risk, a measure of the financial risk exposure of the company) report and circulate it to the traders, the head of your department, and the Chief Risk Officer.

9:00 AM: After taking some time to go through email and enjoy a muffin at your desk, you walk down to the trading floor to meet with a power marketer who wants your help to think through a particularly complex tolling agreement. For most deals, he uses an Excel-based pricing tool you developed last year; however, the proposal on the table has a lot of unique conditions. The two of you work at a white board for an hour or so, drawing illustrative “hockey stick” graphs to conceptually evaluate the contract. One sticking point is that the counterparty proposed a step function for pricing based on power plant output, while your team is more interested in pricing that adjusts more dynamically over time. The power marketer needs specific numerical recommendations from you in two days, so you’ll plan to spend time today and tomorrow building an Excel model to support his transaction negotiations.

10:30 AM: You attend a department meeting which focuses on the plan to convert most of the Excel tools your group has developed in the past into stand-alone Visual Basic applications (to make them run faster and be easier to maintain). Building tools is exciting, so everyone on your team is clamoring to be involved in this initiative. With your excellent knowledge of VBA (which you use to create fancy macros in Excel), you’ll have little problem picking up Visual Basic.

Noon: Head over to the on-site company cafeteria to pick up lunch. You see a bunch of folks from IT, with whom you typically interact by phone. You also run into the CFO, who knows you from when you worked with one of his corporate finance analysts on a special project – you ask him how well the balance sheet risk simulation model you collaborated on is continuing to work for his group.

12:45 PM: One of the natural gas futures traders seems to have found a bug in a pricing tool you developed a few months ago. You are constantly working to improve the analytical tools that your team provides to the trading, power marketing, and risk management groups. As people stress-test the tools over time with new and different transaction parameters, they always find small issues, and this time is no different. You manage to locate the bug, correct the problem, and redistribute the tool to the desk team within a couple of hours.

2:00 PM: You sit down at your own desk to dig into building the quantitative model that you talked with power marketing earlier in the day. Throughout the afternoon, you periodically walk over to a few other analysts’ workstations and trade thoughts with them on the best approach to this tough problem.

3:30 PM: Walk over to the kitchenette on your floor to take a short break and fix a cup of coffee. The CRO, who sits on the same floor but on a different hallway, walks in with a couple of the senior accounting managers, talking animatedly about trading limit policies.

5:00 PM: On your way out for the day, poke your head into your manager’s office to let her know that you’re leaving, and will be on track to finish the transaction model for the power marketer by staying late tomorrow night. It’s convenient that you can manage your own time in this fashion and make it to a concert tonight with friends.

Laura Walker Chung has experience as an analyst in the Quantitative Analytics Group and the energy industry.

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