Realistic take-home practice for data candidates

The idea

Data candidates can grind LeetCode SQL all day and still bomb the take-home, because the take-home tests something no practice site rehearses: a messy multi-table warehouse, an ambiguous business prompt, a time limit, and a written summary that gets judged as hard as the queries. The first realistic rep most candidates get is the one that costs them the offer.

DataExpert proved data professionals pay meaningful money for career-advancing education in this exact niche — but courses teach concepts, not the evaluation format. The wedge is rehearsal: timed challenges with deliberately dirty data, hidden rubrics, and AI-graded feedback on both the SQL and the writing. DuckDB-WASM makes it economically absurd in a good way — the entire warehouse runs in the candidate’s browser tab, so marginal infra cost per user is roughly zero. Nobody owns take-home practice the way LeetCode owns algorithms, and the category name is sitting there unclaimed.

Who pays

Job-hunting analysts and analytics engineers pay $20-30 a month from the same wallet that funds LeetCode Premium — an urgency-driven purchase that starts when the search starts. Churn is structural (people get hired), so the model leans on a steady top of funnel: SEO for interview-prep queries per company archetype, r/dataengineering and r/analytics, and data-career YouTubers and newsletter writers who take affiliate deals. A 3-month bundle matches the typical search length and lifts LTV.

MVP scope

• 10-12 hand-built challenges across two roles and four company archetypes, with seeded messy datasets shipped as Parquet
• In-browser DuckDB-WASM workspace: SQL editor, result grid, timer, markdown summary pane
• Deterministic correctness grading plus Claude rubric feedback on style and written communication
• Feedback report with model answer and progress dashboard
• Stripe billing, one free challenge as the funnel
• Skip for v1: dbt-mode with real dbt parsing (fake it with CTE conventions), Python notebooks, mock interviews, company-specific licensed questions, team/bootcamp plans

Build TakeHomeGym, a web app where data candidates rehearse realistic take-home assignments. Stack: Next.js, DuckDB-WASM running entirely in the browser, Claude API for grading, Stripe for subscriptions.

Core flow: 1) Candidate picks a challenge from a library organized by role (analyst, analytics engineer) and company archetype (marketplace, SaaS, e-commerce, fintech). 2) The challenge loads a messy multi-table dataset — 5-8 tables as Parquet files fetched into DuckDB-WASM — with deliberate realism: duplicate rows, timezone traps, soft-deleted records, a deceptive column name, and an ambiguous prompt like the ones real take-homes use. 3) A timer starts (2-4 hours, pausable on lower tiers). 4) Candidate works in a split-pane workspace: SQL editor with result grid on the left, a written-summary markdown editor on the right, plus a dbt-style challenge mode where they define staging and mart models as CTE chains. 5) On submit, Claude grades against a hidden rubric — correctness checked by comparing query results to reference outputs, then style, edge-case handling, and the quality of the written summary including whether they flagged the ambiguity. 6) Feedback report with rubric scores, model answer, and a diff-style commentary.

Pages: landing, challenge library, workspace, feedback report, progress dashboard, billing.

Non-obvious details: grade correctness deterministically (result-set comparison in DuckDB), use the LLM only for style and writing — never let it judge numbers. Generate datasets with seeded faker scripts so answers stay stable.

Pricing: $24/mo or $59 per 3 months. 1 free challenge.