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We need to collect a database of active Telegram groups and community chats for an investment / crypto / trading audience. This task is focused on Telegram groups and community chats, not Telegram channels. Relevant group types: - crypto communities; - trading communities; - investment communities; - macro / market events communities; - stocks / equities communities; - bonds / fixed income communities; - Polymarket / prediction market communities; - crypto news and market news communities; - event-driven trading communities; - crypto signals / alerts communities; - alpha / research communities focused on markets or investing. A group is qualified only if: - it has recent messages within the last few hours at the moment of checking; - there is real discussion, not only ads or bot posts; - multiple users participate, not only one person/account posting; - people discuss crypto, trading, investing, macro, market events, stocks, bonds, Polymarket or prediction markets; - the group is not spam/scam; - the group is not focused on the Russian market or a Russian-based crypto/investment community. This should be done with software/automation, not only manual browsing. Please apply only if you have experience with Telegram group parsing or can clearly explain how you will collect a large database of qualified Telegram groups. The final result must be provided as one Google Sheet. Required table columns: - group name; - group link; - group category; - members count. Example table structure: group name | group link | group category | members count Group A | group link A | trading | 12,500 Group B | group link B | Polymarket | 8,200 Group C | group link C | macro | 21,000 Group D | group link D | crypto news | 15,400 Group category means the type of group, for example: crypto, trading, investment, macro, stocks, bonds, Polymarket, prediction markets, market events, signals, research. Minimum volume: 1,000+ qualified Telegram groups. Do not add low-quality, inactive, spam/scam, mostly advertising, or irrelevant groups just to reach the number.

We need to collect active Telegram groups and community chats for an investment / crypto / trading audience. This task is focused on Telegram groups, not Telegram channels. The task includes both: - finding relevant Telegram groups; - collecting admin / moderator / community contacts from those groups. Relevant group types: - crypto communities; - trading communities; - investment communities; - macro / market events communities; - stocks / equities communities; - bonds / fixed income communities; - Polymarket / prediction market communities; - crypto news and market news communities; - event-driven trading communities; - crypto signals / alerts communities; - alpha / research communities focused on markets or investing. The group must be active and real. Please check: - recent messages and discussion activity; - whether people ask questions or discuss crypto, trading, investing, macro or market news; - whether the group has visible admins, moderators, owners, community managers, or official team accounts; - whether the group is not spam/scam; - whether the group is not mostly ads. Important: do not add Russian groups or groups focused mainly on the Russian market. We need only contacts with a visible role or access in the group: - admins; - owners; - moderators; - community managers; - official team accounts. Do not add: - regular group members without a role; - bots; - support bots; - accounts without a Telegram contact handle; - duplicates. To find or confirm the right contacts, please check: - the group admin list; - the group description / bio; - pinned messages; - recent group messages from people with admin/moderator labels; - the official project/community channel, if connected to the group; - website or social links, if they help confirm the role. Only add a contact if there is a visible reason to believe this person/account has a role or access in the group. This should be done with software/automation, not only manual browsing. Please apply only if you have experience with Telegram group parsing or can clearly explain how you will collect the groups and admin/moderator contacts. The final result must be provided as one Google Sheet. Required table columns: - Telegram contact handle; - group name; - group link; - contact role; - contact display name; - group category. Example table structure: Telegram contact handle | group name | group link | contact role | contact display name | group category admin contact | Group A | group link A | admin | Alex | trading moderator contact | Group A | group link A | moderator | Maria | trading owner contact | Group A | group link A | owner | John | trading admin contact | Group B | group link B | admin | Team Lead | Polymarket community manager contact | Group B | group link B | community manager | Kate | Polymarket official team account | Group C | group link C | official team account | Team Account | macro Group category means the type of group, for example: crypto, trading, investment, macro, stocks, bonds, Polymarket, prediction markets, market events, signals, research. Contacts should not be mixed randomly. Keep all contacts from the same group together: first all contacts for Group A, then all contacts for Group B, then all contacts for Group C, etc. Minimum volume: 1,000+ qualified Telegram groups. Quality requirement: each group must be relevant, active, not focused on the Russian market, not be a Russian-based crypto/investment community, and have at least one visible admin/moderator/community contact. Do not add low-quality, inactive, spam/scam, mostly advertising, or irrelevant groups just to reach the number.

Education and special skills in IT are not important! It is necessary to remotely test a medical application according to instructions using a camera and microphone. This can be done both from a PC and from a smartphone.

I am looking for a meticulous executor to work with a database of Canadian employers (for Q1 2025). The initial file contains 7,254 rows, but contacts need to be searched for only the filtered part. Stage 1: Database Filtering Filter the initial file and keep only employers with the following NOC codes: 85100, 85101, 85103, 82030, 84120, 63200, 94142, 95107. Stage 2: Contact Search and Table Formatting For each company found, contact details need to be manually searched online. The result should be formatted in an Excel table, sorted by NOC codes. Column Structure in the Final Table (strictly in this order): Farm or Business Name (Company) Province NOC Code Job Title Email (priority for HR, recruiting, or general work) Link to Facebook or Instagram Link to LinkedIn Quality Requirements: Since the niche is specific (agriculture/farms/food industry), companies may have a weak online presence. It is necessary to be able to search for contacts not only on official websites but also through Google Maps, local directories, etc.

Task for those who understand aviation. I have a web list of aircraft accidents. Each of the 900 accidents has a tail number of the crashed aircraft. Next to each tail number, you click the search button, Google search opens, and you look for any 1 high-quality photo of the aircraft with that tail number. Copy the link to that photo and paste it into the same list, just in the links section. And this is done 900 times. Parsing won't work here. We've already tried. Because different sites will + image search may show a different tail number or a random photo. Everything needs to be reviewed and done manually. But if there are suggestions - I would be happy to listen!