Trading-Address Enrichment for UK Limited Companies

330.0 GBP

330.0 GBP peopleperhour Technology & Programming Overseas
12 hour ago

Description

1. Background & Objective
Background: Companies House data only includes registered office addresses. We require the actual trading addresses (principal place(s) of business) for analysis, marketing outreach, or compliance.
Objective: Build a pipeline that takes a list of UK company numbers (and optional SIC codes), and outputs a CSV with:
Company number
Company name
Number of employees
Turnover (where available)
SIC code(s)
Trading address (street, city, postcode)
2. Scope of Work
Core Data Ingestion
Download/ingest the monthly Companies House bulk CSV (or use the Companies House API) to get company number, name, postcode, SIC code(s).
Trading-Address Enrichment
Primary method: Parse iXBRL filings for .
Fallback method: Query a Places‐API (e.g. Google Places or Foursquare) by “company name + postcode” to retrieve formatted address.
Data Merging & Cleanup
Consolidate registered vs. trading address fields.
Standardize address formatting.
Deduplicate and log failures for manual review.
Export & Delivery
Export a final CSV with the key fields.
Provide a short one-page README describing usage and dependencies
4. Required Skills & Experience
Strong Python (or Node.js) coding for data pipelines.
Experience parsing XBRL/iXBRL (e.g. python-iXBRL or equivalent).
Familiar with REST-API consumption (Companies House, Google/Foursquare, OpenCorporates).
Familiarity with web-scraping frameworks (Scrapy, BeautifulSoup, Puppeteer) is a plus.
Data cleansing and address standardization best practices.
Docker and CLI scripting for packaging (optional but preferred).
Milestones:
Core data ingestion + sample of 50 records
iXBRL enrichment + fallback API integration
Data cleanup, export & documentation
Please include in your proposal:
Relevant past projects / GitHub samples (especially XBRL or address-enrichment work).
Confirmation you can deliver the three key deliverables.
Estimated timeline and final fixed-price quote.

关注公众号,不定期副业成功案例分享
Follow WeChat

Success story sharing

Want to stay one step ahead of the latest teleworks?

Subscribe Now

Similar Teleworks

Job Title Crypto Arbitrage Bot Developer with CCXT, AAVE Flash Loans, and Capital Controls Project Overview We are seeking an experienced blockchain developer or quant developer to build a fully automated crypto arbitrage trading bot. The bot should detect and execute arbitrage opportunities across multiple Indian and global exchanges, implement safety and capital controls, and optionally use AAVE Flash Loans to optimize liquidity. Core Objectives 1. Detect arbitrage opportunities across multiple exchanges (e.g., all exchanges that are listed on coingapp 2. Automatically execute trades where the arbitrage profit margin exceeds combined trading + gas fees 3. Ensure trade volume is capped to: - 10% of total portfolio balance - 10% of the lesser volume between the two exchanges 4. Integrate AAVE Flash Loans (optional per opportunity) with up to 10% of total balance allocated to gas fees 5. Use CCXT or equivalent libraries for multi-exchange trading 6. Allow integration with external scanners (e.g., Coingapp) for initial opportunity sourcing 7. Include compounding return logic and daily performance tracking 8. Provide logging, dashboards, and error alerts Example Trade Execution Logic Crypto A is priced at $1.00 on Binance and $1.05 on CoinDCX Binance volume = $100, CoinDCX volume = $50 Total fees = 2.5%, Net profit = 2.5% Bot executes a trade worth $5 (10% of lesser volume, within 10% of portfolio cap) Optional: Uses AAVE Flash Loan if gas fees ≤ 10% of portfolio Tech Stack Preferred - Python (Required) - CCXT (Required) - Web3.py or ethers.js (for AAVE integration) - Pandas/Numpy for calculations - FastAPI / Flask (Optional for interface) - MongoDB or SQLite for logs and trade history - Docker (Optional for deployment) Deliverables - Fully working arbitrage scanner & executor - Config file for setting parameters (threshold %, gas fee %, trade caps) - AAVE Flash Loan integration (configurable switch) - Trade simulator for compounding returns - Logs & alerts (success, failure, skipped trades) - Brief documentation for setup and usage Ideal Candidate Will Have - Strong experience in crypto trading bots - Past work with arbitrage, flash loans, and exchange APIs - Experience with DeFi protocols like AAVE - Familiarity with Indian exchange APIs - Security best practices for handling keys and capital How to Apply Please include: - Links to relevant previous bot projects - Your approach for implementing the trade logic & safety checks - Any challenges you foresee with flash loans
240.0 USD Technology & Programming peopleperhour Overseas
4 days ago