Ask Me Anything: A TWSS Faculty Member on What Separates Good Analysts from Great Ones

The WallStreet School has spent the last several years training students for careers in investment banking, equity research and corporate finance, through programs in CFA, FRM, ACCA and Financial Modeling. Along the way, one question keeps coming up from students far more than any other. What actually separates someone who is good at this job from someone who becomes genuinely great at it.

To answer that, we sat down with Himanshu Jain, co-founder of TWSS and lead faculty for the Financial Modeling program. Before TWSS, Himanshu Jain spent years at McKinsey working on strategy and finance transformation projects for large companies. We asked him some of the toughest questions students, alumni and even working analysts had sent in. 

Here’s what Himanshu Jain had to say, in his own words:

Q1: What’s the one skill that separates a good analyst from a great one?

Judgment. Not Excel speed. Not knowing every formula by heart. Not even accounting fundamentals, though all of that obviously helps.

Let me give you a simple example. I once had two analysts on the same deal team, both building revenue projections for a mid sized FMCG client. Same historical data, both knew their formulas well. One analyst projected 18% growth for next year because that’s roughly what the last three years averaged. The other one looked at the same numbers and noticed something different. Growth had actually been slowing down every year, 24%, then 19%, then 14%. She projected just 11% and flagged that the company’s biggest distributor had recently signed with a competitor.

Guess who was closer when the actual numbers came in six months later.

That’s judgment. It means looking past the average and asking what’s really driving a number, instead of just trusting it. Anyone can learn to build a model. Very few people can tell you whether that model is actually telling the truth.

I saw the exact same pattern at McKinsey, just at a much bigger scale. On one cost project for a manufacturing client, the initial numbers showed a clean 8% reduction in operating costs across all their plants. Dig one layer deeper though and you’d see that number was really being carried by just one efficient plant, while two others were quietly getting more expensive to run. If we had shown that blended average to the client’s board without explaining the real picture, they would have approved a plan that fixed nothing. Clients don’t pay consultants or analysts for that matter, to hand them an average. They’re paying someone to actually look under the hood.

Q2: How’s the current job market looking for finance and analyst roles?

Better than people give it credit for, but also more selective than it used to be five or six years ago.

What I mean is, the number of openings hasn’t dried up. If anything, roles in equity research, financial modeling and corporate finance have grown steadily, especially with more boutique advisory firms and mid market investment banks expanding their India teams. But recruiters today are far more careful about who they hire compared to before. A resume with the right degree used to be enough to get shortlisted. Today it barely gets you a first call.

What’s changed is the depth of screening. Companies would rather hire one strong analyst who can be productive from week one than two average ones they’ll spend six months training. That shift is exactly why practical skill matters so much more now than it did even a few years back.

Q3: What are recruiters actually looking for these days?

Two things mainly. Can this person think clearly under pressure and can they actually build something useful without constant supervision.

I talk to a fair number of hiring managers, at boutique IB firms, at KPO’s doing financial research, at corporate strategy teams. The complaint I hear most often isn’t that candidates lack knowledge. It’s that many candidates can recite formulas and frameworks perfectly in an interview but freeze the moment they’re asked to apply that knowledge to a messy, real world data set. Real client data is never clean. It has gaps, weird one time items, restated numbers from a prior year. Recruiters want to see if you can handle that mess, not just answer textbook questions.

Q4: What should someone expect in a technical interview round for finance roles?

Expect them to hand you a case, not a quiz.

The old style of technical round used to be rapid fire questions. Define EBITDA. What’s the formula for WACC. That still happens, sure, but it’s usually just to filter out people who clearly haven’t done the basics. The real evaluation now almost always involves a case. They’ll give you a company, some numbers, maybe a scenario and ask you to build something on the spot or walk them through your thinking.

What they’re really testing is whether you can structure an unclear problem. Can you figure out what information you actually need, ask the right clarifying questions and build a defensible answer even when you don’t have every single data point you’d like. That’s a very different skill from memorizing formulas and it’s honestly the one thing most college courses don’t teach at all.

Q5: How long does it actually take to get good at financial modeling?

I’ll give you a real number here. We’ve tracked around 400 students who went through our Advanced Financial Modeling program over the last three years. The ones who reach real proficiency, meaning they can build a three statement model without much hand holding, get there in about 90 to 120 days of consistent practice. Not classroom hours. Actual practice.

But there’s a second number that matters even more. It takes closer to 12 to 18 months of real deal or project exposure before someone starts developing actual judgment, the kind I was just talking about. The technical stuff moves fast. Judgment moves slow. Most people give up on building it because there’s no certificate waiting for them at the end of that part.

Q6: What’s the biggest mistake you see in student models?

Plugging in numbers without actually understanding them.

I’ve probably reviewed close to 3,000 student models by now, honestly maybe more. The most common problem isn’t a broken formula or a circular reference, though sure, those happen too. It’s that students often can’t explain why a number is what it is. Ask someone why they picked a 6% terminal growth rate and you’ll get silence. Or worse, “that’s what I saw in another model somewhere.”

A model is only as good as the story behind every assumption in it. If you can’t defend a number in front of a client or an investment committee, that number probably shouldn’t be in your model in the first place.

Q7: Does formal education matter as much as people think or is it overrated?

Overrated, if we’re talking about it as a substitute for actual skill. Not irrelevant though.

I’ve hired analysts straight out of top B-schools who couldn’t build a working debt schedule if their life depended on it and worked with commerce graduates from small colleges who built cleaner models than some CFA charterholders I know. The degree gets you in the door for the interview. What you actually do in the model is what gets you the offer and more importantly, gets you the second project after that.

That said, I’d be lying if I said credentials don’t matter at all. CFA and FRM give you a shared vocabulary and a discipline that’s genuinely hard to build entirely on your own. But they’re a floor, not a ceiling.

Even at McKinsey, where the bar for pedigree is famously high, the people who kept getting staffed on the meatier engagements weren’t always the ones with the flashiest resumes. They were the ones who could sit across from a client’s CFO and actually defend a number without flipping back to their slides for help.

Q8: What do you wish someone had told you when you were starting out?

That being wrong is part of the job. Hiding it is the actual mistake.

Early on at McKinsey, I once built a valuation with an error in the working capital assumptions. It overstated free cash flow by close to 9%. I caught it two days before the client presentation. My first instinct was pure panic, followed right behind by the urge to quietly fix it and just not mention anything. My engagement manager at the time told me something I still repeat to students today. Nobody remembers the analyst who made one mistake. Everyone remembers the one who tried to hide it.

Great analysts get things wrong all the time. What makes them great is catching it early, owning it fast and fixing the process so it doesn’t happen again.

Q9: Any advice for someone stuck between CFA, FRM or a financial modeling certification?

Honestly, that’s the wrong question. It’s not either or.

Think of it this way. CFA gives you breadth across asset classes and valuation theory. FRM sharpens you specifically for risk. Financial modeling training gives you the hands on ability to actually build what all that theory is describing. I’ve seen candidates with a full CFA charter freeze up when asked to build a working LBO from scratch in Excel, simply because the exam never once asked them to do that.

If you’re aiming for equity research, IB or corporate finance roles, I’d genuinely say layer modeling skills on top of whichever charter path you’re already doing, don’t pick one over the other. At TWSS we track this fairly closely and our last cohort data showed candidates with both a modeling certification and an ongoing CFA or FRM track got close to 40% more interview calls than people with only the charter in progress.

Q10: Last one. What’s a habit every great analyst you’ve worked with shares?

They ask “so what” before they ask “what next.”

Most analysts get trained to move fast, build the model, send the model, jump to the next task. The ones who stand out actually pause and ask what the number means for the business decision on the table. A 15% IRR on its own doesn’t tell you much. Whether that’s good or bad depends entirely on the sector, the risk involved and what else you could be doing with that money instead.

That one habit, pausing to actually interpret something instead of just producing it, is the real dividing line I’ve noticed over the years. It’s teachable. Almost nobody teaches it though, because it’s a lot harder to put on a slide than a formula is.

That’s it for this round. If you’ve got a question you wish you’d asked, drop it in the comments or send it directly to TWSS. We’ll try to do this again once results season settles down a bit.