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AI-Native Financial Market Analysis (Expert Testers Needed )

Бюджет: $250.0 FIXED / ⭐ 5.00 (67) United States

financial-analysis, financial-modeling, forecasting, financial-planning

IMPORTANT NOTES: ________________ 1 ) We're not looking for "testers." We're looking for practitioners, people who've felt the pain of Bloomberg terminals, spent nights cleaning mismatched vendor data, or built a backtest only to realize the data had look-ahead bias. 2) If your cover letter doesn't mention at least one specific data platform you've used professionally, we won't be able to consider your application. TASK OVERVIEW: ______________ We're building a deterministic, anti-hallucination financial data platform; a unified 31-schema lake covering market microstructure, macroeconomic data, SEC fundamentals, and alternative flow data. We're inviting a small group of seasoned professionals to stress-test it before our public launch. In exchange, you'll receive compensation, early-access pricing, and a direct line to our founding team. This is not a task for someone who wants to click around an app. We need frank, technically grounded critique. The kind that makes a product better, not the kind that just says "looks good." WHAT YOU'LL BE EVALUATING _________________________ A platform covering four data realms. Below are the raw data types you'll encounter: 1) MARKET MICROSTRUCTURE: Full SIP & OPRA feeds. Stocks/Options Quotes, Trades, Aggregates, Condition Codes, True VWAP, Indices, Market Status 2) MACRO & RATES: Decades of sovereign data. Inflation, Inflation Expectations, Treasury Yields (10-2 spread), Labor Market indicators 3) SEC & FUNDAMENTALS: Normalized EDGAR: 10-K, 8-K, Balance Sheets, Income Statements, Cash Flow, Earnings, Dividends, Ratios, Risk Factors & Categories 4) FLOW & ALTERNATIVE DATA: Short Interest, Short Volume, News sentiment, IPOs, Splits All accessible via a natural language (NLP) interface. WHO WE'RE LOOKING FOR? ______________________ A) QUANTITATIVE STRATEGIST Systematic trader, Python/SQL fluency, formerly at a fund or HFT. Cares about join latency and point-in-time accuracy. B) EQUITY RESEARCH ANALYST Fundamental or factor-based. Uses 10-Ks, flow data, and macro context. Needs cross-referencing across data types. C) FINTECH PM / STARTUP CTO Building a data-intensive product. Constantly evaluating build vs. buy. Needs reliable infrastructure, not another vendor to normalize. D) PORTFOLIO RISK MANAGER Stress-tests against tail events. Needs tick-level data and order book depth, not summary charts that hide liquidity gaps. E) ACADEMIC / QUANT RESEARCHER PhD economist or risk modeler. Needs long-horizon macro + market data for papers and model stress-testing. F) INDEPENDENT QUANT Self-funded. Deep technical skills. Doesn't want to be a data engineer on top of everything else. Familiarity with at least one of the following is mandatory: ___________________________________________ - Bloomberg - FactSet - Databento - ORATS - Alpaca Markets - Refinitiv / LSEG - Polygon.io - Quandl - Intrinio - Massive.com TASK DETAILS: ____________ Both tracks are requested: TRACK 1 - UX & TECHNICAL REVIEW -------------------------------------------- Evaluate the platform as a product: interface, navigation, speed, and reliability. - Navigate the "Main Site" and the "Intelligence Terminal" query interface. - Document friction points, confusing UI elements, or broken flows - Flag any technical bugs, latency issues, or inconsistent behavior - Rate ease of use, onboarding clarity, and documentation quality. TRACK 2 - DOMAIN & BUSINESS REVIEW ---------------------------------------------------- Evaluate the platform against your real professional standards. - Assess data completeness, accuracy, and depth vs. platforms you've used - Identify gaps in schema coverage relative to your actual use cases - Test the NLP interface: does it answer the questions you'd genuinely ask? - Rate each data realm (Macro, Microstructure, SEC, Flow) by relevance to your work - Tell us what would need to be true for you to switch from your current setup - Correlate any SEC-level query (e.g., risk factor sentiment) with flow/market data. Does it hold up? DELIVERABLE & COMPENSATION ___________________________ - A completed structured feedback report covering your assigned tracks - Approximately 3–5 hours of platform use and 1 hour of structured writeup. - Template provided on onboarding. - Compensation is a fixed fee per completed, high-quality submission. - Testers will receive early-access pricing when we launch. NOTE: _____ We may reach out to exceptional testers for an optional 30-minute follow-up call. Our goal is to build long-term relationships with the people whose opinions actually matter.
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