Freelance Data Analysis Jobs

Create report about Blockchain analysis / forensic investigation

Need someone to write a professional report about a hack from a few years ago in 2022 Need it to look professional tracing information If you know how to use tools like chanalysis and have access to this that would be good. It only involves a few addresses to trace on the terra blockchain / UST currency

opportunity

Data needed for care homes

im looking for Data of all Nursing Home,Care homes, Supported living locations and any other Care settings in this sector, with client name, address, email addresses and Registered manager. current and in date.

Build webscraper to collect data from outlet menus

I have a list of appr. 50.000 outlets, of which I want to have the menu information scraped cleansed and organised (see FACT DIM below). Assignment is to receive a working and tested code for doing that, perphaps for a smal sample of 100 outlets or so to see that it's working. Lump sum proposal please, needs to be ready asap. Best regards, Sander -------------- CREATE TABLE public.outlet ( outlet_id bigint GENERATED ALWAYS AS IDENTITY NOT NULL, naam text NOT NULL, plaats text, website_url text, segment text, status text NOT NULL DEFAULT 'actief'::text CHECK (status = ANY (ARRAY['actief'::text, 'inactief'::text])), created_at timestamp with time zone NOT NULL DEFAULT now(), updated_at timestamp with time zone NOT NULL DEFAULT now(), CONSTRAINT outlet_pkey PRIMARY KEY (outlet_id) ); CREATE TABLE public.menu_source ( source_id bigint GENERATED ALWAYS AS IDENTITY NOT NULL, outlet_id bigint NOT NULL, pagina_type text, url text NOT NULL, domain text, bestandstype text CHECK (bestandstype = ANY (ARRAY['html'::text, 'pdf'::text, 'image'::text])), confidence real, is_active boolean NOT NULL DEFAULT true, created_at timestamp with time zone NOT NULL DEFAULT now(), CONSTRAINT menu_source_pkey PRIMARY KEY (source_id), CONSTRAINT menu_source_outlet_id_fkey FOREIGN KEY (outlet_id) REFERENCES public.outlet(outlet_id) ); CREATE TABLE public.crawl_run ( run_id bigint GENERATED ALWAYS AS IDENTITY NOT NULL, source_id bigint NOT NULL, crawled_at timestamp with time zone NOT NULL DEFAULT now(), http_status integer, etag text, last_modified text, sha256 text, parse_status text NOT NULL DEFAULT 'pending'::text CHECK (parse_status = ANY (ARRAY['pending'::text, 'ok'::text, 'partial'::text, 'failed'::text, 'not_modified'::text])), parser_version text, raw_ref text, CONSTRAINT crawl_run_pkey PRIMARY KEY (run_id), CONSTRAINT crawl_run_source_id_fkey FOREIGN KEY (source_id) REFERENCES public.menu_source(source_id) ); CREATE TABLE public.menu_item ( menuitem_id bigint GENERATED ALWAYS AS IDENTITY NOT NULL, run_id bigint NOT NULL, categorie text, product text NOT NULL, beschrijving text, prijs numeric, valuta text NOT NULL DEFAULT 'EUR'::text, volume text, merk text, merkeigenaar text, positie integer, confidence real, CONSTRAINT menu_item_pkey PRIMARY KEY (menuitem_id), CONSTRAINT menu_item_run_id_fkey FOREIGN KEY (run_id) REFERENCES public.crawl_run(run_id) ); CREATE TABLE public.change_event ( event_id bigint GENERATED ALWAYS AS IDENTITY NOT NULL, outlet_id bigint NOT NULL, source_id bigint, oud_menuitem_id bigint, nieuw_menuitem_id bigint, detectiedatum timestamp with time zone NOT NULL DEFAULT now(), event_type text NOT NULL CHECK (event_type = ANY (ARRAY['product_toegevoegd'::text, 'product_verwijderd'::text, 'prijs_verhoogd'::text, 'prijs_verlaagd'::text, 'brand_switch'::text, 'menu_redesign'::text])), oude_waarde text, nieuwe_waarde text, ai_interpretatie text, impact text CHECK (impact = ANY (ARRAY['hoog'::text, 'midden'::text, 'laag'::text])), opportunity_score integer CHECK (opportunity_score >= 0 AND opportunity_score <= 100), aanbevolen_actie text, bevestigd_runs integer NOT NULL DEFAULT 1, status text NOT NULL DEFAULT 'nieuw'::text CHECK (status = ANY (ARRAY['nieuw'::text, 'bekeken'::text, 'afgehandeld'::text, 'false_positive'::text])), CONSTRAINT change_event_pkey PRIMARY KEY (event_id), CONSTRAINT change_event_outlet_id_fkey FOREIGN KEY (outlet_id) REFERENCES public.outlet(outlet_id), CONSTRAINT change_event_source_id_fkey FOREIGN KEY (source_id) REFERENCES public.menu_source(source_id), CONSTRAINT change_event_oud_menuitem_id_fkey FOREIGN KEY (oud_menuitem_id) REFERENCES public.menu_item(menuitem_id), CONSTRAINT change_event_nieuw_menuitem_id_fkey FOREIGN KEY (nieuw_menuitem_id) REFERENCES public.menu_item(menuitem_id) );

opportunity

Hospitality analyst — serviced-apartment feasibility & valuation

I have been commisdioned developer-sponsor of a consented, ready-to-build serviced-apartment resort in a UK island/coastal leisure market. An operating model and investor memorandum already exist — I need an experienced hospitality real-estate analyst to independently validate and deepen the numbers ahead of partner due diligence, and ideally put their name to the analysis. Full detail and data room shared under NDA only. **Scope** (hourly, or as fixed deliverables): - STR/CoStar competitive-set and achieved-performance benchmarking (RevPAR/ADR/occupancy) - Penetration / fair-share analysis vs the competitive set - USALI departmental P&L — fresh build or stress-test of my existing model - 10-year DCF to stabilisation, giving a DCF value alongside the existing cap-rate value - A short, citable written commentary for inclusion in the memorandum **You:** - 3+ years hospitality valuation/consulting (HVS, Savills, Colliers, CBRE Hotels, JLL or similar) - STR/CoStar access or a clear route to a custom market pull - Strong USALI and hotel/serviced-apartment DCF modelling - MRICS a plus — independent, named authorship is valued - UK experience essential; Scottish/leisure-resort exposure ideal **Engagement:** Remote, hourly. ~15–30 hours to start, scope to extend. **NDA required before any project detail is shared.** Please send a redacted sample of comparable work and your hourly rate

CRM Data Cleanup Support

We're seeking a freelancer to help organize and clean customer records. The work includes reviewing entries, removing duplicates, correcting formatting, and updating information as instructed. Responsibilities Review customer records Remove duplicate entries Correct data formatting Update information where required If you have strong attention to detail and can deliver accurate work, we'd be happy to hear from you.

opportunity

Short-form video editor for a futures-trading analysis brand

We're Beneath The Book (@beneaththebook) a futures-trading analysis brand covering ES & NQ through order-flow and structural levels. We publish daily educational market analysis. Our voice is honest and no-hype: "levels, not predictions." We're not a get-rich-quick signals account, and our content reflects that. What we need: A short-form video editor to turn our daily raw material (chart screenshots, level cards, screen recordings, and a script/voiceover we provide) into engaging 20–40 second vertical videos for TikTok, Instagram Reels, and X. The work, per video: A scroll-stopping hook in the first 1–2 seconds (on-screen text) Motion that holds attention: draw-on annotations, zoom-into-the-level, marker drops timed to the narration Burned-in captions (most viewers watch muted) Clean branded end-card with handle and a soft call-to-action Platform-specific exports (9:16 for TikTok and Reels, plus a feed-friendly cut) We provide the script, voiceover, and the levels/branding you handle the edit, motion, captions, and exports. The trading voice stays with us. You're a fit if you: Edit short-form for retention, not just polish (CapCut/Premiere) Can make data or charts engaging please show examples where you made something analytical or "boring" hold attention Can deliver fast turnaround (ideally same-day, since this is daily content) Understand TikTok/Reels hook-and-retention mechanics To apply: Share a portfolio, ideally with finance, data, or explainer-style work Tell us how you'd hook a viewer in the first second of a trading video Note your turnaround time and per-video rate First step: a paid test piece one card + one script → one finished video before any ongoing arrangement. Note: This is educational market-analysis content. No performance or profit claims feature in the work.

opportunity

Data Scraper

I need Desicion maker emails, phone numbers business name, all checked that are working of restaurants in Alicante, Valencia cities in Spain and the small towns around them.

Adobe Lightroom Specialist to create Meta Data

I shoot Bodybuilding shows and need help speeding up my Workflow. I currently use Adobe Lightroom Classic and could use help adding the metadata to each photo. (Name of competitors). It is easy use facial recognition to get most of the meta data. However, When they turn around and view their backs the only reference I have is the numbered button they have on their Bikini/trunks. They typically have two buttons. one on the front and one on the back. I typically have anywhere from 7,000-12,000 pics per show. Anyone out there good at this? Looking for a 2 day turnaround. Please reply with estimate etc. Of course I would have to share the library. Thanks for you time. Price TBD

Icelandic Speakers for Data Audio Collection Project

We’re currently inviting native Icelandic speakers from Iceland to join a paid, fully remote AI audio task. Who we’re looking for: Icelandic speakers from Iceland Task details: 10 short phone calls with an AI bot $18per call ($180 total) Around 30 minutes to complete 100% remote No experience needed How to get started: Complete a quick 30-second Icelandic verification on Click worker (required) Once approved, you’ll get access to the paid audio task

Audience Data Buy (USA) Job Seeker

I am looking for data on 25,000 individuals of Nigerian origin who are currently living in the USA and are interested in transitioning into IT careers. This audience includes nurses, Uber drivers, plumbers, caregivers, warehouse workers, and other professionals from blue-collar backgrounds who are looking to move into the IT industry.

Seeking eCommerce Beta Testers

Beta Tester - Optagen Portal & Integrations What you’re testing The Optagen portal lets you manage multiple stores by bringing together data from your commerce, analytics, accounting, inventory, and CRM systems. It creates a single ranked action list, with each recommendation labeled for trust and checked against real results. We need beta testers to use the portal with real store data and identify what breaks, what’s slow, what’s missing, and what doesn’t match reality. Integration coverage required You will test syncing and data accuracy across these integrations: Commerce platforms: Shopify, BigCommerce, WooCommerce, Etsy Analytics: Google Analytics 4, Search Console Shipping/3PL: ShipBob, ShipStation, Easyship Inventory systems: Cin7, Katana Accounting: QuickBooks, Xero Marketing/CRM: Klaviyo You don’t need to use every integration—just test the ones you already use. We’re aiming for each tester to cover at least 3 or 4 integrations from different categories. What we’re asking 1. Sync completeness: Check if all the expected fields from each integration show up in the portal. Are SKU, pricing, margin, sales, traffic, inventory, and competitor data there? 2. Refresh latency: See how long it takes for changes in your source system (like a price update in Shopify or a GA4 event) to show up in the ranked plan. 3. Data accuracy: Choose 5 to 10 data points you can check in both your source system and Optagen. Do they match? 4. Signal read accuracy: The portal calculates metrics such as AI visibility, SKU margins, demand signals, returns concentration, pricing elasticity, and competitor share of voice. Check these against your store. Do they make sense? Can you find the data sources if you look for them? 5. Ranked plan stability: Run the same store scan twice in one week. Does the ranked plan update based on new data, or does it stay the same? Are the revenue-impact numbers realistic? What we’re not asking * Testing the governed execution agent (scheduled to ship later; currently in development) * Load testing or scale testing * Security testing or pen testing * UX/design feedback (we’ll gather that separately) Timeline and access * Beta runs from [DATE] to [DATE] * You’ll get portal access for your own stores, using your real data—not test data. * We’ll keep an eye on logs and collect diagnostics if something fails. Please report any issues as they happen via a feedback button. * We’ll have a weekly sync call to talk about any blockers or patterns you notice. Who should apply * You run 1-5 stores across 2+ of these platforms. * You can verify data accuracy (you know your actual margins, traffic, and sales numbers) * You’re willing to spend 2-4 hours per week auditing sync health and data correctness. * You’re okay with bugs and incomplete features since this is a beta test. When you apply, please indicate: * Which platforms you currently use (Shopify, BigCommerce, WooCommerce, Etsy etc.) * Rough store size (monthly revenue or annual, average order value, SKU count) * Any specific data quality concerns you have with your current setup

opportunity

Yorkshire Data Scraper

We are looking to purchase or commission an up-to-date, high-quality B2B marketing database covering Yorkshire and surrounding areas The data will be used to market Material Handling Equipment, Forklift Trucks, Warehouse Equipment, Scrubber Dryers and Industrial Sweepers, so the data must be relevant to companies with factories, warehouses, depots, production sites, industrial premises or operational facilities We are not looking for a basic scraped company list. We require verified, marketing-ready data with named contacts and valid emails wherever possible Include companies located in the following postcode areas: BB, BD, BL, HG, LS, HX, HD, WF, DN, S, SK The address should relate to the actual trading, manufacturing, warehouse, depot or operational site, not just a registered office address where possible. Include companies in the following sectors: 10 – Manufacture of food products 11 – Manufacture of beverages 13 – Manufacture of textiles 14 – Manufacture of wearing apparel 15 – Manufacture of leather and related products 16 – Manufacture of wood and products of wood and cork, except furniture 17 – Manufacture of paper and paper products 18 – Printing and reproduction of recorded media 19 – Manufacture of coke and refined petroleum products 20 – Manufacture of chemicals and chemical products 21 – Manufacture of pharmaceutical products and preparations 22 – Manufacture of rubber and plastic products 23 – Manufacture of other non-metallic mineral products 24 – Manufacture of basic metals 25 – Manufacture of fabricated metal products, except machinery and equipment 26 – Manufacture of computer, electronic and optical products 27 – Manufacture of electrical equipment 28 – Manufacture of machinery and equipment n.e.c. 29 – Manufacture of motor vehicles, trailers and semi-trailers 30 – Manufacture of other transport equipment 31 – Manufacture of furniture 38 – Waste collection, treatment and disposal activities; materials recovery 41 – Construction of buildings 52 – Warehousing and support activities for transportation We want to focus mainly on companies with 1–199 employees Please include employee banding, for example: 1–10 11–25 26–50 51–100 101–199 200+, only if highly relevant For every company, we require the following where available: Company type/industry Company name SIC code Website Employee banding Site address split into address line 1, line 2, line 3, town/city, county and postcode Postcode area Company telephone number Company LinkedIn page Date verified Contact Requirements We require named decision-maker contacts wherever possible. Priority contacts include: Operations Manager Warehouse Manager Purchasing Manager Procurement Manager Facilities Manager Site Manager Production Manager Logistics Manager Managing Director Director General Manager For each contact, please provide: Contact name Job title Direct email address Generic email address, only where no direct email is available Email type: Direct or Generic Email validation status Landline number Direct dial, where available Mobile number, where available Contact LinkedIn profile Date contact was last verified Email Quality Requirements Valid, up-to-date emails are essential. Direct business emails are strongly preferred. Generic emails should only be used where a verified named contact email cannot be found. Please separate direct and generic emails into separate columns. Do not mix them in the same field. We do not want large volumes of guessed, invalid, risky or unverified email addresses. Please confirm what email validation method or tool has been used and include the validation result in the data. Acceptable generic emails, only where direct contacts are unavailable, may include: info@ sales@ enquiries@ purchasing@ procurement@ operations@ Please do not include personal email addresses such as Gmail, Outlook, Hotmail or Yahoo. The data must be: Recently verified Relevant to the requested postcode areas Relevant to the requested industries Deduplicated Suitable for B2B marketing use Free from dormant or dissolved companies Free from irrelevant businesses Focused on genuine operating companies Accurate and cleanly formatted Please do not apply if you are only able to provide basic scraped Companies House data without named contacts and verified emails. Before placing the full order, please provide a sample of 50–100 records. The sample should include a mix of postcode areas, sectors, employee sizes, direct contacts and generic contacts where direct emails are unavailable. The sample will be checked for relevance, accuracy, direct email quality, duplicate records, address quality and suitability for marketing material handling and floor care equipment. We expect there to be over **2,500 companies** matching the requested criteria. Please provide an estimated breakdown by: Postcode area Industry / SIC code Employee banding Number of direct contacts Number of generic contacts Number of validated emails

Cold Call Insurance Data

I am looking for an experienced telemarketer to dial B2C data that will be provided. I would like to trial 2000 records to see how they can perform. Data capture will need to include; Insured, Uninsured, Insured through work then insurance provider i.e AXA, Aviva etc then renewal date and interested not interested. I am a broker in Private health insurance so will all need to be compliant etc. Of course i'd love everyone to be ready to discuss, transferred or appointment to be booked but as long as we can cleanse the data that is my main focus at this stage. if successful this will be an ongoing project for the foreseeable. This project is for real humans only with clear English as this is a very sceptical industry and I do not feel it would be very successful otherwise. Please offer a fair price on the service and happy for 2 prices, one for a trial and one for an ongoing contract I look forward to hearing from you Ben

Social media analysis and video cutting/creation

I need someone to find social media videos - that are football based ones, ideally trending, that can be slow motion perhaps that I can copy and repurpose. I need 20 different ones. short simple job. videos need to ideally be 25-60secs duration. can be some up to 90 seconds long with same video clip repurposed perhaps. thefutbolguru is an instagram account to see similar videos but they are all too short in duration. I want videos that I can either paste text onto or VoiceOver.

Data Center - 2D and 3D design

I need a designer that is specialised in the design of Data Center (20MW upto 150MW). Trackrecord and esperience necessary.

Product Catalog Spreadsheet Data Cleansing Description

Looking for a meticulous data entry freelancer to clean and format an existing product catalog spreadsheet for an internal review. All data is fully provided; no external sourcing or account creation is required. Responsibilities Organize product descriptions into correct columns. Clean up formatting and align pricing fields. Identify and remove duplicate rows. A Note for Applicants If you are detail-oriented and enjoy turning messy data into a structured spreadsheet, please send through your proposal. Looking forward to your applications!

Create automated planning application spreadsheet

I am looking for someone to create an automated spreadsheet/report that pulls the previous week’s UK planning applications from the UK PlanIt data/API. The purpose of the report is to help identify potential trade opportunities for builders, loft conversion companies, kitchen/renovation firms, roofers and other home improvement trades. I need the spreadsheet to be refreshable each week, so I can update it with the latest planning applications and then export or share the data with ChatGPT for analysis. What I need is a spreadsheet system, ideally in Google Sheets or Excel, that can: 1. Pull planning application data from UK PlanIt. 2. Refresh the report weekly to show the previous 7 days of applications. 3. Cover all UK counties / planning areas, not just one local authority. 4. Handle multiple planning authorities within each county where needed. 5. Pull clean, structured data into a spreadsheet. 6. Allow me to filter by county, planning authority, date, application type and likely trade opportunity. 7. Create summary tabs that make the data easy to review. 8. Be simple enough for a non-technical user to refresh each week. **Important functionality required:** The spreadsheet should include: * A refresh button or clear refresh process. * A date range selector, ideally defaulting to the last 7 days. * County / area filtering. * Planning authority filtering. * Keyword filtering for relevant trade opportunities. * Automatic categorisation where possible, for example: * Extensions * Loft conversions * Garage conversions * Renovations/refurbishments * Kitchens * Roofing * Outbuildings * Commercial fit-outs * Other building works * A clean export tab that can be copied into ChatGPT for analysis. * Basic error handling if the API limit is reached or if a request fails. * A simple instruction tab explaining how I refresh and use the report. **Suggested spreadsheet tabs:** 1. **Instructions** Simple user guide explaining how to refresh the data and use the spreadsheet. 2. **Settings / Control Panel** Date range, counties/areas to include, keywords, refresh controls and any API settings. 3. **Raw Planning Applications** The unedited data pulled from PlanIt. 4. **Cleaned Applications** Clean version of the data with standardised columns. 5. **Trade Categorisation** Applications categorised by likely trade relevance. 6. **County Summary** Number of opportunities by county and trade type. 7. **Planning Authority Summary** Number of opportunities by local authority. 8. **ChatGPT Export** A clean tab designed specifically so I can copy/export the data and ask ChatGPT to analyse it. **Required data fields:** Where available from PlanIt, I would like the spreadsheet to include: * Application name/reference * Planning authority * County / area * Application start date * Address * Description * Application type * Development type * Status * Decision, if available * Applicant / agent details, if available * Link to planning application * Latitude / longitude, if available * Last scraped / last changed date * Suggested trade category * Opportunity score, if possible **Trade opportunity scoring:** Ideally, I would like a simple scoring system to highlight the best opportunities. For example: * High relevance: extension, loft conversion, conversion, major renovation * Medium relevance: alterations, outbuildings, roof works, garage conversion * Low relevance: tree works, signage, minor admin applications, discharge of conditions I am happy for the freelancer to suggest the best scoring approach. **Technical requirements:** The freelancer should be comfortable working with: * APIs * Google Sheets Apps Script and/or Excel Power Query * CSV/JSON data imports * Pagination * Rate limits * Data cleaning * Building refreshable dashboards/reports The PlanIt API has paging and request limits, so the system must be built responsibly and should not rely on one huge request. **End goal:** Each week I want to be able to refresh the spreadsheet, see the latest planning applications across all counties, identify the best trade opportunities, and then ask ChatGPT to analyse the data by county, trade type and opportunity quality. **Deliverables:** 1. A working Google Sheet or Excel workbook. 2. Automated or semi-automated weekly refresh process. 3. All required tabs and filters. 4. Clean data structure ready for ChatGPT analysis. 5. Simple instructions for use. 6. A short handover call or written walkthrough. 7. Notes on any limitations of the PlanIt API or recommended future improvements. **Please include in your response:** * Whether you recommend Google Sheets or Excel for this. * Examples of similar API/spreadsheet automation work. * How you would handle all counties and multiple planning authorities. * How you would manage API limits and pagination. * Estimated delivery time. * Fixed price quote.

SLR Screening Assistant Needed (Media/Linguistics PhD)

I'm a PhD candidate conducting a systematic literature review as part of my doctoral thesis, in Critical Discourse Analysis of English-language online news reporting. I'm looking for a freelancer to support the mechanical/administrative side of the SLR process. This is NOT a request to write or synthesise the literature review. All inclusion/exclusion decisions, quality appraisal, and synthesis are done by me. Tasks include: Running literature searches across specified databases (Scopus, Web of Science, Google Scholar and Elicit) using search strings I provide Exporting and organising search results into a shared spreadsheet Logging hit counts per database/string for PRISMA reporting Extracting basic bibliographic and methodological details from articles into a template I provide (author, year, method, findings summary) Applying my stated inclusion/exclusion criteria to flag candidates for my review (final decisions remain mine) Ideal candidate: Experience with systematic reviews or PRISMA methodology preferred Familiarity with Critical Discourse Analysis or discourse-based methods is a plus but not essential Comfortable reading academic abstracts in media/communication studies or applied linguistics Comfortable working from detailed instructions and templates Strong attention to detail and organisation Background in social sciences, media studies, or linguistics welcome but not required What I will provide: Search strings and database list Inclusion/exclusion criteria Quality appraisal template Data extraction template Timeline: 3–4 weeks from start date, with a brief check-in at the halfway point.

opportunity

Commodity Trading CRM

Seeking an experienced developer familiar with Replit to support and finalize a bespoke Commodity Trading CRM for international markets. The product, initiated on Replit, requires assistance with feature completion, integration, data workflows, user interface refinement, and performance optimization. Ideal candidate will demonstrate Replit proficiency, backend and frontend competence, familiarity with trading workflows, secure data handling, and a collaborative approach to meet delivery timelines and quality standards.

Data Scraping - Competitor feedback

I need someone who can look at competitor recommendation websites for certain businesses and then work out who their customers are from people who have left comments of that business. This role is best suited to someone in the UK or at least very familiar with what names are common / uncommon in the UK. There will be names that are too generic and you cannot find the exact person for the business on companies house (like John Smith, Adam Cox, Joe Frost) , so they can be skipped. I need you to find exact businesses and be 100% sure that the company you find belongs to the person who left the comment. This task will take accuracy and care, rather than quickly gathering as much data that wont be needed. The company on Companies House needs to show it is ACTIVE, not anything else. Otherwise move on to the next record. EXAMPLE For example there is a comment from someone called Louise Lamberti (which isnt a very common name) Then i searched the name on Companies House and find the company she has: https://find-and-update.company-information.service.gov.uk/officers/0jr3CzJOVyJKznJUNuQQgwaAZH8/appointments There is no one else with this name as an Officer on Companies House so i am pretty sure this is the company it relates to. Then i need someone to gather as much information as possible on the business which the attached spreadsheet. I need named business email addresses and contact numbers - no personal email addresses! Tab 1 holds information for the business that we need Tab 2 are the different company names that you can search their feedback If you need more clarification please let me know. Looking for someone to work on this for an ongoing basis - will pay £10 per hour and expect to get around 40 records per hour. PLEASE COULD YOU SEND ME AN EXAMPLE ON THE ATTACHED SPREADSHEET OF 2 RECORDS THAT YOU FIND SO I CAN TEST THE QUALITY OF YOUR WORK BEFORE I ACCEPT. Happy to go through a video call to explain in more detail if this is required. £10 per 100 records - ongoing project