We're hiring a Business Analyst to be the data and decisions brain of an early-stage SaaS.
You'll define what we measure, build the dashboards we trust, run the analyses that make the founder change their mind, and turn raw product and revenue data into clear recommendations. You'll work directly with the founder, sit in on every strategic decision, and help us avoid the most common early-stage failure mode — moving fast with the wrong metrics.
This is a full-time, on-site role at our Amritsar office.
About Kwill
Kwill is the client portal for the world's service businesses — one branded experience for proposals, e-signatures, invoices, and Stripe-powered payments. Our customers' clients experience it as the business's own brand, not Kwill's.
We're built global-first, with real users in 40+ countries. The product is real, growing, and generating real revenue. We have customer-facing data, payment data, product-usage data, marketing data, and support data. We do not yet have a single person whose full-time job is to make sense of all of it.
That's the role.
Why this role exists
Most early-stage SaaS companies die from one of two things: building the wrong thing, or scaling the wrong thing. Both are data problems disguised as product problems. The founder has good instincts, but instincts at our stage need to be checked against the data weekly — activation, retention, channel attribution, pricing pressure, payment success rates, churn signals, expansion patterns.
Today we're tracking the basics in scattered tools. We need someone to pull it together, define what good looks like, and make the metrics a live part of every decision the team makes.
You will be that person — half analyst, half decision support, half product detective. (Yes, that's three halves. It's a startup.)
What you'll ownMetrics & dashboards
- Define our North Star metric and the supporting KPI tree (acquisition → activation → retention → expansion).
- Build and maintain the single source of truth dashboard the whole team checks every morning.
- Set up data plumbing: product analytics (Plausible + product events), payments (Stripe), customer support, and internal tooling, into one queryable layer.
- Document every metric definition so "activation" or "churn" means the same thing in every meeting.
Analyses that change decisions
- Weekly: cohort retention, channel attribution, signup → activation funnel, payment success rates, support ticket clustering.
- Monthly: deep-dive analyses on the question the founder is currently losing sleep over. Examples we'd ask in your first 90 days:
- "Which of our channels brings users who actually activate?"
- "What does the 'aha moment' look like, and how do we get more users to it?"
- "Why do users in country X churn 2× faster than in country Y?"
- "What's the right pricing tier mix, and where should we test changes?"
- Quarterly: business reviews, board-ready summaries (when we have a board), competitive intelligence reports.
Experiments
- Design and run A/B tests on pricing, onboarding, messaging, and growth experiments.
- Define hypotheses, sample sizes, and success metrics before the test ships.
- Honest write-ups after every test — including the ones that fail.
Financial and growth modeling
- Maintain the unit economics model: CAC, LTV, payback, gross margin per cohort.
- Build forecasts the team actually trusts — not optimistic boardroom numbers, real planning numbers.
- Help the founder think through pricing changes, regional expansion, and channel investment decisions with real numbers under each option.
Decision support
- Turn raw data into clear, written recommendations. Memos, not just charts.
- Sit in on product, marketing, and strategy meetings — bring the data, name the trade-offs, push back when the instinct doesn't match the numbers.
- Help every team make better-informed decisions. You are not a request queue.
Areas of focus in your first six months
- Activation. Define it precisely. Measure it. Move it.
- Channel attribution. Where do our paying users actually come from? Replace gut with proof.
- Pricing analysis. Pressure-test the current tiers; surface where we're leaving money on the table or pushing users away.
- Churn detective work. Voluntary vs involuntary; per-region; per-plan. Find the signals that predict churn 30 days early.
- Global expansion analytics. Which countries should we double down on? Which payment methods unlock which markets?
- Funnel optimisation across the marketing-to-product handoff. Sign-up → portal setup → first proposal → first invoice → first payment.
We're looking for someone who…
- Has 2–5 years of analyst experience, ideally in SaaS, fintech, or product-led growth companies. Operating experience inside a startup beats consulting experience for this role.
- Writes strong SQL. You can query a Postgres database without LLM hand-holding. You know how to think about joins, window functions, cohort tables. This is table stakes.
- Is expert with spreadsheets. Sheets/Excel modelling is a daily tool. Pivot tables, dynamic formulas, basic scenario modelling.
- Thinks in metrics frameworks. You understand retention curves, cohort tables, funnel mechanics, MRR/ARR decomposition, contribution margin, LTV/CAC.
- Writes clear memos. A good analysis ends with a recommendation, written down, in 1–2 pages a busy founder can read in 5 minutes.
- Asks better questions than the requester. When someone asks "what's our churn?", you ask "voluntary or involuntary, by plan, by region, by cohort?" — and explain why the answer matters.
- Is honest with the numbers. You don't massage data to fit a narrative. You name the limits and confidence levels.
- Speaks fluent English in writing. Hindi and Punjabi are bonuses for working with our local team.
- Cares about the user. Behind every row in the table is a real freelancer trying to get paid. The good analyst never forgets this.
You do not need:
- A statistics or CS degree. Strong self-taught analysts and former engineers count just as much.
- Python or R fluency (though it helps — see Nice to have).
- Big-company FP&A or BCG-style consulting experience. That work-style often doesn't fit early-stage.
- To already live in Amritsar. If you're nearby (Jalandhar, Ludhiana, Chandigarh, Delhi) and willing to relocate, we'll help.
Nice to have, not required
- Python or R for analyses spreadsheets can't comfortably do (large data, statistical tests, mild ML).
- Experience with Stripe data (subscriptions, invoices, charges, MRR reconciliation).
- Experience with Supabase / Postgres schemas, RLS, or similar.
- Experience with a BI tool — Metabase, Looker Studio, Mode, Hex, Sigma, or similar.
- Experience with a product analytics tool — PostHog, Amplitude, Mixpanel, or Plausible at scale.
- Experience designing and shipping A/B tests with proper statistical rigor.
- A taste for financial modeling — three-statement, unit economics, scenario planning.
- A side project, public dashboard, blog post, or analysis you can point to.
- A second or third language. We're global; cultural fluency matters.
Our data stack
You'll work with most of this on day one and learn the rest as we go.
- Application database: Supabase (Postgres + Row-Level Security).
- Payments: Stripe (subscriptions, charges, invoices, Connect).
- Product analytics: Plausible (we may add PostHog or similar).
- Marketing analytics: Plausible + native channel analytics (LinkedIn, X, Meta, TikTok when active).
- Spreadsheets: Google Sheets is the default modelling tool.
- BI: to be selected. You'll have a say.
- Internal tooling: lightweight admin panels in our app for ops-level data.
A typical week
- One 15-min daily standup with the founder (in person).
- 8–12 hours of focused analysis and modelling — your deep work.
- 6–10 hours of dashboard maintenance, ad-hoc queries, and decision-support requests.
- 3–5 hours of stakeholder meetings with product, marketing, and the founder.
- One weekly written memo: top three insights from this week, what they mean, what we should do.
You set the rhythm. We protect deep-work blocks.
What you get
- Real ownership. You are the analytics decision-maker, not a request-queue. Your judgement is trusted.
- A flat, fast team. Direct access to the founder, weekly product and growth decisions you're in the room for.
- A competitive salary for Amritsar, generously benchmarked. Discussed openly in the first call.
- Meaningful equity. This is real ownership in a company with real customers and revenue. We will explain the structure clearly and answer every question.
- Generous, flexible paid time off plus paid Indian holidays. We expect you to take real rest.
- Annual learning budget for courses, books, conferences, or anything that grows you.
- Working equipment — laptop, monitor, large external screen, whatever you need for serious analytical work.
- A monthly health stipend toward your health coverage.
- A small relocation stipend if you're moving for this role.
- A clear growth path. Strong performance moves you toward Head of Analytics, Head of Growth, or Director of Strategy as we scale. We say this because it has happened to others on the team.
Logistics
LocationOn-site at our Amritsar office, India.
Schedule In-office, Monday to Friday. Standard working hours.
HoursFull-time, ~40 hrs/week. Flexible within reason.
CompensationCompetitive base + meaningful equity. Discussed openly in the first call.
Start date As soon as you can. Notice periods are respected.
Trial period. Standard 3-month performance review.
Pay: ₹200,000.00 - ₹400,000.00 per year
Work Location: In person
