Fact Checking Projects

Data Engineer(Salesforce CRM)

We are looking for an experienced Data Engineer to help clean, standardize, and structure large volumes of real estate and regulatory compliance data. This role focuses on transforming messy, inconsistent datasets into a reliable and scalable data foundation that supports reporting, compliance tracking, and future automation. You will work closely with our business and technical teams to understand data logic, resolve inconsistencies, and design a clean, structured data environment. Responsibilities -Review and analyze existing datasets (leases, units, tenants, occupancy, rent, compliance) -Identify inconsistencies, duplicates, and missing or conflicting records -Standardize naming conventions, unique IDs, and relationships -Clean and transform data from spreadsheets, CSVs, and system exports -Build master datasets for properties, units, tenants, and leases -Develop repeatable data-cleaning workflows or pipelines -Implement data validation and quality checks -Create documentation (data dictionary, mappings, business rules) -Generate exception reports for data issues requiring review Required Skills -Strong experience with SQL and Python -Experience with ETL / data transformation workflows -Solid understanding of data modeling and relational databases -Experience cleaning messy, multi-source datasets -Strong knowledge of data validation and data quality practices -Ability to work independently and communicate clearly

opportunity

AI Coordinator

AI Operations Expert for Multi-Channel Ecommerce Overview I run a fast-growing online brand selling through multiple storefronts. I need help from an AI operations expert to streamline our marketing and operations across all platforms. Scope of work - Clone and redeploy marketing assets across Amazon, Etsy, TikTok Shop, website, eBay, Facebook, and Instagram. - Design automated funnels turning social followers into customers using chatbots and dynamic offers. - Monitor and optimize AI stack, including data pipelines, prompt tweaking, insights surfacing, and documentation. - Ensure platforms pass brand-review spot checks and deploy unified creative assets. - Develop automated funnels ready for attribution from first social touch to checkout. - Create a clear dashboard or weekly report with performance metrics and system alerts. - Document step-by-step SOPs for junior team members to run basics. References - Current tools: Shopify, Zapier, Klaviyo, Meta Ads Manager, Amazon Ads, ChatGPT; Open to Make, Tray.io, Manychat. Additional information I'd love to hear how you can prove a more efficient mix of tools. Let's set up a call and map the roadmap together. Company details - I run a fast-growing online brand with storefronts on Amazon, Etsy, TikTok Shop, website, eBay, Facebook, and Instagram. - Ecommerce Automation Type Data syncing, Marketing campaign, CRM workflows, Task automation, Email automation ntegration Points Website, Shopify, Social Media, Email Platforms , , , Websites, , , Instagram, Shopify, Zapier Ideal candidate (Optional) Budget and timeline (Mandatory)

Data engineer

We are seeking an experienced Data Engineer to help organize, clean, and structure complex real estate and regulatory compliance data across multiple sources. This role focuses on transforming inconsistent datasets related to leases, occupancy, tenants, and rent information into a reliable and scalable data foundation. The ideal candidate will review existing data, identify quality issues such as duplication and missing fields, and design standardized schemas and relationships. You will build transformation workflows to clean and normalize data from spreadsheets, databases, and system exports. In this role, you will create master datasets for properties, units, households, leases, and compliance tracking while implementing validation rules and exception reporting. You will also document data definitions, mapping logic, and business rules to support transparency and long-term maintainability, while collaborating with stakeholders to translate operational requirements into structured data models. Strong proficiency in SQL and Python is required, along with hands-on experience in ETL/ELT workflows and relational data modeling. Experience working with messy, Excel-heavy datasets and building data quality checks is essential, and familiarity with tools like dbt, Airflow, or cloud platforms such as Snowflake or BigQuery is highly preferred. Success in this role means delivering a clear, consistent source of truth for lease and occupancy data, reducing inconsistencies, and preparing the data environment for reporting, automation, and future product development.

Prospect Intelligence Analyst | Research Assistant

ROLE OVERVIEW Our firm helps small service businesses in the US and UK identify and fix operational revenue leaks — the gaps that cause them to lose enquiries and bookings without realizing it. You sit at the front of our Prospect Machine. Each week you research small businesses, identify their primary revenue leak, score them, enrich decision maker contacts, and populate our structured prospecting tracker. Your output feeds directly to our Cold Caller and Business Systems Consultants. This is not a data entry role. It requires pattern recognition, fast decision-making from limited information, and the discipline to work at consistent pace to a fixed weekly deadline. CORE RESPONSIBILITIES • Source 150–200 raw businesses per week using scraping tools provided by company • Filter to 120–150 qualified SMBs • Review each business's online digital presence — website, booking system, social pages, and online reputation — and conduct test calls outside office hours to assess missed call risk and after-hours responsiveness. Identify the primary operational revenue leak based on what the evidence shows • Find and verify the decision maker via enrichment tools provided by company • Score each lead, flag Priority Leads, and escalate leads immediately • Populate the B2B Prospecting Tracker • Submit all deliverables via agreed upon platform and time. Onboarding Ramp Week 1— 50–60 leads, research and tracker only. Full SOP and training provided. Quality standards apply from day one. Week 2 onwards — Cold call script prep for top 20 Priority Leads added. Week 3 onwards — Industry community and directory identification added. REQUIREMENTS • Experience in B2B lead research, business intelligence, or structured data research • Able to make fast, confident decisions from publicly available data • Strong attention to detail — accurate entries matter more than perfect ones • Comfortable following a structured SOP independently, without frequent check-ins • Clear written and spoken English, with prompt communication COMPENSATION & STRUCTURE • $17.00/hr · 15 hrs/week · ~$255/week • Performance review at 45 days — rate increase available for strong performers HOW TO APPLY Begin your application with the word SIGNAL — applications that don't will not be reviewed. Then answer these two questions: 1. Describe a research or data project where you worked to a consistent weekly output target. What tools did you use and what was your weekly volume? 2. You're researching a dental practice. Their website has no online booking system — new patients are instructed to call during office hours only. There is no contact form and no alternative way to enquire outside of calling. In two to three sentences: identify the primary revenue leak, explain why it matters commercially, and give this lead a score out of 10 with a one-sentence justification. Note Question 2 has a clear correct answer. We are looking for specific, evidenced reasoning — not a general description of the problem.

opportunity

AI Monitoring Platform for UK Company Alerts

Project Title: AI Monitoring Platform for UK Company Financial Distress & Insolvency Alerts (SIC-Based) Project Overview: I’m looking for an experienced developer (or small team) to build an AI-powered monitoring platform or intelligent agent that tracks UK companies within pre-defined SIC codes and automatically alerts me when there are signs of financial distress or insolvency. The system should continuously monitor company data, detect risk signals, and provide both real-time alerts and structured reporting. Core Objective: To proactively identify companies within selected industries that are: Experiencing financial decline (e.g. credit score drop) Entering insolvency processes (e.g. notice of intent to appoint administrators) Showing early warning signs of distress Key Functional Requirements: 1. Company Data Collection The platform must: Pull and maintain a live database of UK companies filtered by selected SIC codes Sources should include: Companies House API Commercial data providers such as Creditsafe, Experian, Dun & Bradstreet (or similar via API) 2. Data Monitoring (Automated & Ongoing) The system should periodically (daily or weekly) re-check and update the following: Credit score (via commercial providers) Filing timeliness (overdue accounts, confirmation statements, etc.) Insolvency indicators: Notice of Intent to Appoint Administrators Administration Liquidation CVAs Director changes: Appointments Resignations 3. Financial Data Enrichment (Important) Where available, the platform should also pull and display from latest filed accounts: Turnover / Revenue Balance sheet data (e.g. total assets, liabilities, net assets) This can be sourced from: Companies House filings (accounts data) Or via commercial data providers if more structured/standardised 4. Alert Triggers The platform must generate alerts when: A company’s credit score drops by 5% or more Include the exact percentage drop in the alert Any insolvency-related event is detected, including: Notice of Intent for Administration Administration Liquidation 5. Alert Delivery Alerts should be sent via: Email (minimum requirement) Ideally also: Slack / Microsoft Teams Web dashboard notifications 6. Reporting (Key Requirement) The system must automatically generate and send: Daily report Weekly report Monthly report Each report should be delivered as a spreadsheet (Excel or Google Sheets) and include: Columns to include (minimum): Company Name Company Number SIC Code Date of event/activity Type of event (e.g. credit score drop, insolvency notice, director change) Previous credit score New credit score % change in credit score Filing status (on time / overdue) Insolvency status Director changes (summary) Turnover (latest available) Key balance sheet figures (assets, liabilities, net position) Reports should clearly show date-stamped activity and allow filtering/sorting. 7. Dashboard / Interface (Preferred) A simple dashboard to: View and filter companies by SIC code Track alerts and risk levels View historical changes and trends Export data 8. AI / Intelligence Layer (Optional but Preferred) Identify early warning signals before insolvency Highlight patterns (e.g. repeated late filings + score decline) Rank companies by risk level or likelihood of distress Technical Requirements: Experience integrating APIs (Companies House + credit agencies) Ability to build automated data polling (scheduled jobs) Cloud-based database and infrastructure Alerting and reporting automation Scalable architecture Data Sources (Must Be Used): Companies House API (free, primary source) Commercial credit data providers such as: Creditsafe Experian Business Dun & Bradstreet Please advise on: Best provider(s) to use API access requirements Ongoing data/licensing costs Deliverables: Fully functioning monitoring and alert system Automated reporting (daily, weekly, monthly) Spreadsheet output format Documentation and user guidance Ability to adjust SIC codes and thresholds Optional ongoing support Nice to Have: CRM integration (e.g. Zoho) Webhooks for automation Customisable reporting Data visualisation Budget & Timeline: Open to proposals – please include: Estimated cost Timeline Recommended tech stack Relevant experience / similar projects

opportunity

Tidy the server from X-ransom attack

Hello, Our Wordpress website was attacked by x-ransom. We have a backup of the WP and the database dump. We have detected some corrupted files there but it seems that there are still some left that were not detected. It has to be tidy after the attack. It’s an internet shop with uploads files of around 100GB. It’s stored on a private hosting in LV. What is done do far: 1. Update WordPress Version 2. Use z’d updateSecure WP-Admin Login Credentials 3. Set Up Safelist and Blocklist for the Admin Page 4. Use Trusted WordPress Themes 5. Install SSL Certificate 6. Remove Unused WordPress Plugins and Themes 1. Enable Two-Factor Authentication for WP-Admin 2. Back Up WordPress 3. Limit Login Attempts 4. Change the WordPress Login Page URL 5. Log Idle Users Out Automatically 6. Monitor User Activity 7. Check for Malware - found several none-Wordpress specious files and plugins. Deleted them. 1. Disable PHP Error Reporting 3. Turn File Editing Off 4. Restrict Access Using the .htaccess File 5. Change the Default WordPress Database Prefix - not done 6. Disable XML-RPC 7. Hide the WordPress Version 8. Block Hotlinking - not done 9. Manage File Permissions not done After making the list, we received another x-ransome attack. I suspect he has a server level access not only wp level. If you apply, you need to be a server security and a Wordpress specialist. Please, quote for the job.

Review CV and cover letter for Mental Health clinician role

I want to apply for a Mental Health clinician role and I have an up-to-date CV and cover letter, I would like someone to review it to see if it can be improved and to check the grammar. Also, for the role, I have 2 short questions that would like someone to review the answers to.