Data Science Developer for a SaaS / RE App work on UIUX | API [Documentation / Research]

Data Science Developer — Job Description Project: Real Estate Investment Network — Web Platform (Phases 2–5) Engagement type: Fixed-price, milestone-based Total budget: $500 fixed price Estimate roughly $15–20/hour depending on actual hours logged. Start: Joins the project at Phase 2 and works through Phase 5 About the project We're building a web platform that connects real estate developers, investors, brokers, and lenders — combining a networking/CRM layer, a secure deal data room, an underwriting sandbox, and (eventually) an AI assistant layered over user data. You'll be joining a small team already in progress; a lead developer and a finance-focused contractor are working the same phases alongside you. What you'll work on Phase 2 — Foundations ($150) Early data-architecture and schema planning ahead of the Phase 3 data room and underwriting build, so the structures we build next don't need rework Phase 3 — Data Room & Underwriting ($100) Structure the data room's storage schema (Excel/PPT/PDF/property/deal files) Design the underwriting data model and rate-cap calculation logic Plan the Cloudflare R2 storage integration for secure document storage Phase 4 — Advanced Underwriting & Analytics ($100) Build the underwriting data storage and aggregation layer Produce area/range/market aggregate statistics Handle data parsing across inconsistent uploaded file formats Implement sensitivity analysis and underwriting insight/flag logic Feed a data pipeline into the analytics dashboard Phase 5 — AI / Bot Layer ($150) Wire up the data plumbing for a “bring your own AI” agent (connecting to OpenAI, Claude, Gemini, etc.) Build personalized recommendation logic and an explainability layer (why a recommendation was made) Build the search/summarize pipeline the AI agent uses over permitted user data Payment milestones Milestone Phase Amount 1 Phase 2 $150 2 Phase 3 $100 3 Phase 4 $100 4 Phase 5 $150 Each milestone is released on delivery/approval of that phase's data-science scope above. What we're looking for Strong data modeling / schema design skills Experience with financial or real-estate data (underwriting, rate calculations) a plus Comfortable working with cloud object storage (Cloudflare R2, S3, or similar) Experience integrating LLM APIs (OpenAI, Anthropic, Google) for recommendation/search features Able to work independently against a phased spec and hit milestone deadlines Deliverables Per-phase outputs Phase 2: Draft data model / schema notes Phase 3: Data room storage schema; underwriting data model and rate-cap calculation logic; Cloudflare R2 storage integration spec Phase 4: Data aggregation/analysis layer; sensitivity-analysis model; dashboard data pipeline Phase 5: AI integration layer; recommendation engine; explainability output Collaboration & technical outputs Cross-checks: Work with the Finance specialist (Excel lead) and the client's Finance Head to confirm data outputs match the expected financial results Architecture: An advanced Data Flow Diagram (DFD) covering the full pipeline — uploads, storage, underwriting, analytics, and the AI layer API: API layer/spec connecting the Excel-based finance models, the platform database, and cloud storage Data pipeline: Documented conversion logic for moving data from Excel models into structured storage on AWS/Cloudflare R2 Data Security Write-up: Covering storage, access control, and encryption of platform data Data classification: A data-point labeling and classification scheme (public / private / internal), feeding into the Phase 4 data-classification rules Onboarding: An onboarding guide for the data work, so a future contractor or the in-house team can pick it up Research documentation: Write-up of findings and research from the engagement (e.g. storage options evaluated, AI providers compared) Basic test/validation notes confirming the underwriting and aggregation logic against sample data before each milestone sign-off A brief handover write-up at the end of Phase 5 summarizing the data architecture and AI integration for whoever maintains it next Explain how you'd calculate a rate cap for a real estate loan, and what happens to that calculation if the underlying index rate moves after the deal closes. This will be needed to be presented via Data / Lead Developer on SaaS If you had to cap AI spend per user without making the AI feature useless, how would you set that cap and what would make you raise or lower it later? This work but done by lead developer. What we're looking for Strong data modeling / schema design skills Experience with financial or real-estate data (underwriting, rate calculations) a plus Comfortable working with cloud object storage (Cloudflare R2, S3, or similar) Experience integrating LLM APIs (OpenAI, Anthropic, Google) for recommendation/search features Able to work independently against a phased spec and hit milestone deadlines Deliverables Work with Financial Excel person and Financial Head for assistance that deliverables to make sure their outcome is complete DFD Advanced API Math Excel to Data to AWS Data Security Writeup Data Points Labeling and classification Onboarding to Data work Documentation of Finding and research What tech stack and database are currently being used, and how much of the Phase 2 architecture/schema has already been defined? Will sample underwriting models, Excel files, and expected financial outputs be provided for validating rate-cap, sensitivity, and aggregation logic? What level of implementation is expected for the $500 budget: production-ready code, architecture/spec documentation, prototypes, or a combination? How should responsibilities be divided between the Data Science Developer, lead developer, Finance specialist, and Finance Head during Phases 2–5? For Phase 5, do you already have a preferred LLM/RAG architecture, vector database, and permission model, or should I recommend and design these?