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Should you quit your job to study? A runway worksheet

PK
Pankit Kumar
Sr. Data Scientist at Parexel (a Goldman Sachs–backed company) · 27 September 2026 · 4 min read
In this article (7 sections)

Related programme: the Data Science course (6 months; ₹1,30,000 (inclusive of GST) · EMI from ₹5,000/month).

The short answer

Quit your job to study data science only if your savings cover the full course, a realistic job search and an emergency buffer — calculated from your own spending, not a guess — and only if your current job genuinely leaves no time to study. For most people with rent, EMIs or dependants, studying part-time while employed is the safer choice. The worksheet below turns that into numbers you can check.

Step 1: write down your real monthly outflow

Use three months of bank and UPI statements, not memory. People who estimate usually leave out irregular items.

LineWhat to includeYour figure
FixedRent or home-loan EMI, other EMIs, insurance premiums, school fees, money sent home
Essential variableGroceries, utilities, phone and internet, transport, medicines
Irregular, averagedFestivals, weddings, travel home, repairs — take the yearly total and divide by 12
Health coverIf your employer's group insurance ends when you resign, the cost of a personal policy
Study costsCourse instalments still due, laptop, internet upgrade

The health-cover line is the one most often missed. Check your company's policy document for when cover ends after the last working day.

Step 2: decide the months you must cover

Runway is not just the course. It is three periods added together:

  • Course months. From the programme's published duration — for example 6 months for a data science track.
  • Search months. Time from finishing to a first salary credit. Nobody can promise this number. Plan for at least six months, and more if you are changing field entirely.
  • Buffer. Two to three months of outflow held back for a medical bill or family emergency. This money is never counted as available.

Step 3: run the worksheet

Replace every number below with your own. All figures here are hypothetical.

python
# Hypothetical inputs - replace with your own
monthly_outflow = 32_000          # from Step 1, excluding study costs
study_one_off = 60_000            # course balance + laptop etc. (your quote)
liquid_savings = 4_50_000         # savings you can actually withdraw
untouchable = 1_00_000            # money you will not spend: dependants, debt safety
course_months = 6
search_months = 6
buffer_months = 3
side_income_monthly = 5_000       # freelance, tuition, rent received - be honest

available = liquid_savings - untouchable - study_one_off
net_burn = monthly_outflow - side_income_monthly
needed = net_burn * (course_months + search_months + buffer_months)
runway_months = available / net_burn

print(f"Available for living costs : Rs {available:,}")
print(f"Net monthly burn           : Rs {net_burn:,}")
print(f"Needed for plan            : Rs {needed:,}")
print(f"Runway                     : {runway_months:.1f} months")
print(f"Plan needs                 : {course_months + search_months + buffer_months} months")

shortfall = needed - available
if shortfall > 0:
    print(f"Short by Rs {shortfall:,} - do not resign on these numbers")
else:
    print(f"Covered with Rs {-shortfall:,} to spare")

assert round(runway_months, 1) == 10.7
assert shortfall == 1_15_000

In this example the reader has ₹4,50,000 saved and still falls ₹1,15,000 short of a 15-month plan. Their runway is about 10.7 months — enough for the course and four months of searching, with no buffer. That is precisely the situation that turns into panic applications around month ten.

Step 4: read the result

Runway compared with planWhat it suggests
Less than course monthsDo not resign. Study part-time or delay.
Covers course, not the searchResign only if you can return to similar work quickly; otherwise part-time.
Covers course and search, no bufferBorderline. Reduce outflow or build buffer for a few months first.
Covers everything with buffer intactFinancially possible. Now check the non-financial questions below.

Step 5: set a stop-loss date before you resign

Write down, in advance, the date on which you will start applying for jobs in your old field if you have no data offer. Put it where your family can see it. For the example above, that date would be around month nine of the plan, leaving a buffer to cover the gap while you look. Deciding this in advance, while calm, is far easier than deciding it at month nine with a low balance.

Options short of quitting

Before resigning, ask your employer about each of these. Some are more available than people assume:

  1. 1Moving to a shift or role with predictable hours, even at the same pay, to free up evenings.
  2. 2Unpaid leave or a sabbatical for the most intensive part of the course. Check your HR policy for whether this exists and what it does to your service continuity.
  3. 3An internal move toward data work — building reports for your own team is experience you can put on a resume.
  4. 4Reduced hours or contract work in your current field, if your industry supports it.

Non-financial questions

  • Is the job the real obstacle, or is it the commute, the phone at night, or low energy? Some of those have smaller fixes.
  • Will a gap on your resume be easy to explain? A completed programme with portfolio projects helps; a gap with nothing to show does not.
  • Does your household agree with the plan and the stop-loss date?

Data science learning fits alongside work if the weekly load is realistic; see a 10-hours-a-week timetable for what that looks like. The Data Science programme is live online with recordings, which is what makes part-time study workable, and you can ask a counsellor for current fees and instalment options to fill in the study-costs line honestly.

Frequently asked questions

How many months of savings do I need before quitting to study?

Enough to cover the whole course, the job search after it and a buffer, using your real monthly spending. A useful rule is to plan for the course length plus at least six months of searching plus a cushion for emergencies, then check whether your savings cover that without touching money set aside for dependants or debt repayments.

Is it better to study part-time while working?

For most people with fixed expenses, yes. Studying 10 to 15 hours a week alongside a job is slower but keeps income, keeps your work history continuous and removes the pressure of a shrinking bank balance. Quitting makes sense mainly when your job leaves no usable time or energy at all and your runway is long.

PK
Pankit Kumar
Lead Instructor, NeuraPath Academy

Pankit Kumar has 10 years in Data Science & AI, building and shipping production systems in regulated pharma and clinical environments. He is a freelance trainer at Boston Institute of Analytics, AnalytixLabs and Scaler, and has taught this material to thousands of working professionals.

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