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    Challenges/Golden Analytics/Full Stack Engineer/Household Portfolio Rebalancer

    Household Portfolio Rebalancer

    Full Stack
    Fintech
    Data Modeling
    Agentic Development
    Estimated Time:
    2 hours
    Status:Not started

    What You'll Be Doing

    Description

    Someone manages their household's investments across multiple broker accounts and wants to keep their portfolio aligned to a chosen asset-allocation target — and to be able to change that target over time. Their broker only gives them a flat CSV export of raw positions (symbol-level holdings), not a view organized the way they actually think about their money.

    Your job is to close four gaps:

    1. The data isn't in a usable shape. The provided CSV is a flat, symbol-level export across multiple accounts. Turn it into something organized the way the user actually thinks about their money.
    2. There's no concept of a target. The user thinks in terms of asset classes (US Equity, International, Gold, Cash, Treasuries, etc.) and target percentages, but the brokerage only shows individual ticker holdings. You'll need to design how tickers map to asset classes — the sample data does not come with this mapping; that design is part of the challenge.
    3. Rebalancing math is tedious and error-prone by hand. Given a current allocation and a target allocation, figure out exactly which symbols to buy and sell — and how much — to reach the target. Cash cannot move between accounts, so each account must be rebalanced independently, funded and absorbed only by its own money-market/cash position.
    4. Some accounts are more liquid than others. The user may prefer to hold more cash in certain accounts (e.g., maximize cash in a brokerage account rather than a retirement account) because that account is more accessible. Your solution should account for this preference.

    Build a working tool — not a script or notebook — where a user can see their current allocation, edit a target allocation, and get back the exact set of transactions needed to reach it.

    Constraints to Consider

    • No paid or proprietary services required. Your solution must run locally from documented setup steps — no infrastructure budget assumed.
    • The CSV export format is fixed. You cannot change what the brokerage sends. Your solution must ingest the provided format as-is.
    • Cash cannot move between accounts. Each account rebalances independently, funded only by its own money-market/cash position — never assume you can use one account's cash to fund a trade in another.
    • 120-minute total budget, including your video. Prioritize a complete, working core experience over a partially-built comprehensive one.

    AI Usage Guidance

    We expect you to use AI tools while building this. We evaluate how you use them — not whether you used them. Evidence of iteration, redirection, and critical evaluation scores higher than a polished output with no process documentation. Note: this challenge does not require your solution to call an AI API at runtime — the AI evaluation is entirely about your build process.

    The single highest-signal indicator: your video answer to the mandatory AI question. If you cannot name a specific moment where you redirected AI output, evaluators will assume you did not.

    Mandatory AI question for your video: Walk me through one moment where you disagreed with, pushed back on, or redirected what the AI gave you — and what you did instead. Name the specific moment. Explain what the AI produced that didn't meet the bar, what you did differently, and why.

    Speak naturally. Communication is assessed on clarity of technical ideas and logical structure — not verbal polish, accent, or filler words.

    Submission: Upload each deliverable as a separate file directly on the Provn platform: your primary artifact, your README document (Sections A, B, and C), and your video walkthrough (MP4 or MOV).

    What You'll Accomplish

    Demonstrate ability to transform raw, unstructured financial data into a coherent, usable domain model

    Build a full-stack tool that turns an ambiguous financial requirement into a usable interface

    Design and implement a constrained rebalancing algorithm that respects real-world limitations (per-account cash isolation, liquidity preference)

    Communicate architectural decisions and trade-offs clearly to a technical audience

    Demonstrate effective, critical collaboration with AI tools throughout the build process

    How Your Work Will Be Scored

    Data Modeling & Rebalancing Logic (30%): A strong submission correctly computes per-account rebalancing trades that respect cash isolation, and implements the liquidity preference in a way that generalizes beyond the single example described.Full-Stack Execution & Product Craft (25%): A strong submission is a working, usable end-to-end tool — not a script — that makes a dense financial dataset easy to understand and trust.Technical Communication & Decision-Making (15%): A strong submission clearly explains specific architectural decisions and trade-offs, in both the README and the video.AI Fluency (20%): A strong submission shows iterative, critical collaboration with AI — catching and correcting AI mistakes, not accepting first-pass output.Resume & Background (10%): Assessed from your submitted resume, not your challenge artifacts — evaluated separately for directly relevant full-stack and AI-building experience.

    What to Submit

    No submission guidelines provided.

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