Extract Healthcare VC Data

@Tanmoy236

Hi There! I specialize in financial data extraction and VC database research with 9+ years of experience working with PitchBook-style datasets, structured exports, and clean Excel reporting. Here’s how I can help: 1. Run structured PitchBook screening using your defined geography, size, stage, and sector filters 2. Extract and organize healthcare VC funds, portfolio companies, and metadata into a clean Excel workbook 3. Ensure de-duplication, consistent formatting, and validated PitchBook URLs 4. Build a screened-out tab with clear exclusion reasoning for full auditability Do you already have confirmed stage and vintage filters, or should I propose an optimized screening structure based on healthcare VC norms?

@justmian876

As the head of BN-Droids Digital Services with over five years of experience in Full-Stack Web Development, I am highly capable of assisting you with your intricate data pulling project. Data is a central aspect of our daily operations and I have an experienced team who specialize in web data scraping, capable of extracting over a million data entries per day. Our focus on accuracy in our processes and quality output makes us the perfect match for this project.

@ayazakhtar75

As an experienced data analyst with over 16 years of experience, I have developed a set of skills that can be instrumental in ensuring the success of your project. My proficiency with Excel and Google Sheets is extensive, ranging from automation to data processing, allowing me to extract and manipulate significant amounts of data proficiently. Moreover, my command over macros, VBA and Google Apps Script enables me to automate tasks and minimize human error. I am particularly well-versed in exporting large datasets to Excel without formatting drifts, an ability that will prove pivotal in generating an error-free workbook for you. De-duplication, consistent formatting and comprehensive filtering according to your needs are second nature to me. Accuracy being paramount in such a significant dataset extraction, rest assured that I'd put in the double-checks required on names, tags and links before each delivery to ensure absolutely precise results. Through our collaboration, I pledge to not only provide the valuable insight you seek but also streamline your workflows, increase efficiency and identify new grounds for growth – all while keeping your business goals at the forefront of my methodologies. Choose Ayaz's Data Analysis Solutions for an unmatched advantage in tackling this nuanced venture capital data extraction task.

@sunmoon25

Hello, I can give you a comprehensive list of apollo leads. Will you try this ? Thanks. ....................................

@OutsourceMan

⭐⭐⭐⭐⭐ 0As the founder of CnELIndia, a leading web and app development company, I am confident in my team's ability to successfully execute your project. With our robust skill set in web scraping and search, we'll deftly run a targeted filter on PitchBook using your specified parameters: geographic regions, fund size, investment stages, and vintage. Moreover, our experience in handling large datasets with advanced tools like Excel without compromising on formatting or data quality will ensure successful extraction and systematic organization of the data in the required format. Our long-standing dedication to achieving diverse web-based goals for our clients is demonstrated through our proficiency. We understand that accuracy is key for this task, which is why we will double-check names, tags, and links to eliminate any possibility of errors. Furthermore, rest assured that we will deliver a de-duplicated and consistently formatted Excel workbook that is compatible for your downstream work. Ultimately, what sets us apart is our drive for innovation. While this task solely requires data extraction from PitchBook, we aim to go above and beyond by offering you viable tech solutions that can aid in analyzing the acquired data. With CnELIndia you can be confident that your project is in experienced hands capable of delivering optimal results in a timely manner.

@eshA0010

With my strong background in data management and extensive expertise in Excel, I am confident in my ability to tackle your complex data extraction project. Specializing in data analysis, entry, extraction, processing and being skilled at web scraping, I assure you that I can handle significant tasks and deliver accurate results. Moreover, having a vast experience in extracting large datasets from online platforms such as PitchBook and organizing them into user-friendly formats like Excel without any formatting drift,is definitely an advantage for me here. My familiarity with the software coupled with meticulous attention to detail will guarantee the elimination of any duplication while consistently formatting the sheet according to your requirements. Additionally, my fast communication, on-time delivery reputation and dedication to providing quality work sets me apart from other freelancers. As your project scope doesn't require analysis but only clean extraction which mandates thorough checking of names, tags and links; my skill of double-checking even the minutest details before delivery comes very handy. In conclusion,I would love to take charge of this task because when it comes to extracting intricate datasets accurately, I never disappoint! Let's make this happen together!

@emilesd617

Hi, I am a data research specialist with 8 years of rich experience in data extraction and database management. I am familiar with PitchBook, Excel, Data Processing, Data Entry, Data Extraction, Web Search, Data Collection, Data Management, Data Analysis, and healthcare VC research. For this project, the most important thing is to pull accurate PitchBook data for healthcare-focused VC funds under $100M across North America, Europe, and Asia-Pacific, then organize the results into a clean Excel workbook with Funds, Portfolio Companies, and Screened Out tabs, fully de-duplicated and ready for your downstream analysis. I'm an individual freelancer and can work on any time zone you want. Please contact me with the best time for you to have a quick chat. Looking forward to discussing more details. Thanks. Emile.

@Ekarthaan

Hi mn378, last week i did a similar project and i am confident to handle this really well. I have active PitchBook access and know the export quirks, so I’ll deliver a clean, ready-to-use workbook with zero drift and no dupes. i would like to know the below. - Please confirm the exact stage filters and vintage years; should vintage be final close year or first close? - For healthcare scope, do you want only funds tagged as healthcare-focused, or also generalists with ≥1 healthcare deal? I think we should. - Include PitchBook Fund ID and Company ID columns to lock de-duplication and stable joins. - Export as CSV in controlled batches, then normalize types/formatting in Excel/Power Query to avoid formatting drift. Lets follow a plan like this. - I set the screen: NA/EU/APAC + fund size < $100M; I add stage/vintage once you confirm. - I export Funds with all PB fields, append an “Applied Filters” column, clean names, and de-dupe by Fund ID. - I pull linked Portfolio Companies with descriptions, sector tags, live PB URLs; standardize and de-dupe by Company ID. - I share a 5‑fund sample for acceptance; then finish full pull, log “Screened Out” with reasons, and re-check names/tags/links. Accuracy over speed, always. May I know if you are the project owner or part of the direct client team, because I usually work directly with the customer and do not engage through agents, brokers, or middle parties. Thank you for understanding. Don’t mind.

@codefusion53

Hi, I can help with this PitchBook data extraction and Excel structuring task, including clean fund screening, portfolio company mapping, deduplication, and formatting. I have experience with data extraction, Excel workbook preparation, database research, VC and investment datasets, record validation, and structured exports for downstream analysis. I can follow your PitchBook screen criteria across North America, Europe, and Asia-Pacific, apply the fund size, stage, and vintage filters, and organize the output into the three requested tabs: Funds, Portfolio Companies, and Screened Out. I will make sure each record includes the applied filters, relevant PitchBook fields, healthcare scope validation, portfolio links, exclusion reasons, consistent formatting, and duplicate checks. I can also provide the five-fund sample first so you can confirm the structure before the full pull. Best, Justin

@rezamahi

With 4+ years of experience in data research, lead generation, and large-scale dataset extraction, I can complete this PitchBook data pull accurately and deliver a clean, well-structured Excel workbook ready for downstream analysis. I am experienced in working with investment, venture capital, and company datasets, ensuring data quality, de-duplication, and consistent formatting across large exports. I will apply the required filters for geography (North America, Europe, and Asia-Pacific), fund size (<$100M), and the stage/vintage criteria once confirmed. Deliverables: • Funds tab – complete qualifying VC fund dataset with export fields and applied filters • Portfolio Companies tab – linked portfolio companies with descriptions, healthcare sector tags, and PitchBook URLs • Screened Out tab – excluded funds with documented exclusion reasons • Fully de-duplicated and quality-checked Excel workbook Before completing the full project, I can provide a sample of five qualifying funds for validation to ensure the screening methodology aligns with your expectations. I understand that accuracy is critical for this project and will carefully verify fund names, sector classifications, portfolio mappings, and links before final delivery. I am ready to begin immediately.

@C0RETECHIES

Hi there, I understand the workflow. You need a precise data pull from PitchBook, starting with a multi-filter screen (geography, fund size, stage, vintage) to identify relevant healthcare VC funds. From this qualified list, the core task is to systematically extract both the fund details and the complete list of their associated portfolio companies. The process requires careful logging of any funds reviewed but excluded to ensure a transparent audit trail. Technical approach: - Execute the screen on PitchBook using your fixed filters (geography, size) and the pending stage/vintage criteria. - Conduct a two-pass extraction: 1) capture the qualifying funds, 2) iterate through that list to pull all linked portfolio company data. - Structure and clean the exported data, ensuring no formatting drift or character encoding issues. - Consolidate everything into the specified three-tab Excel workbook, running a final de-duplication pass. Core modules: - Funds Database: A clean, structured list of all VC funds matching your exact criteria. - Portfolio Company Linkage: A comprehensive mapping of every company to its parent fund, including URLs and sector tags. - Exclusion Log: A transparent record of funds reviewed but disqualified, with the specific reason noted for each. Implementation strategy: First, we'll confirm the final stage and vintage thresholds. I'll then extract the 5-fund sample for your review. Upon your approval of the sample's structure and accuracy, I will proceed with the full data extraction, cleansing, and assembly of the final workbook. Regards, Rohit

@manish1808

Hello!! I would love to work on your project and have the skills required to accomplish the task. Pls have a look at my reviews. I aim for perfection and will make sure the delivered work is 100% error free. Looking forward to work with you!!

@nfatima41

Hello, I understand you need a clean and accurate PitchBook data extraction focused on healthcare-focused VC funds across North America, Europe, and Asia-Pacific, limited to funds under USD 100M. I have experience working with large datasets in Excel and can deliver a well-structured, de-duplicated workbook with: Funds tab containing all qualifying VC funds and applied filters Portfolio Companies tab with descriptions, sector tags, and PitchBook URLs Screened Out tab documenting excluded funds and exclusion reasons I will ensure consistent formatting, verify names, tags, and links, and provide a 5-fund sample for approval before completing the full dataset. Best Regards, Noor Fatima

@Georgeoustar

Hi, I’ve handled PitchBook research and investor data extraction projects involving VC fund screens, portfolio company exports, healthcare sector filtering, deduplication, and clean Excel workbook delivery. I’ve also worked on similar private-market mapping tasks where funds had to be filtered by geography, fund size, stage, vintage, sector focus, and then cross-checked so screened-out records were documented with clear exclusion reasons. For your healthcare VC landscape pull, I can run the PitchBook screen across North America, Europe, and Asia-Pacific, limit funds to under USD 100M, apply your confirmed stage and vintage thresholds, and prepare the Excel workbook with Funds, Portfolio Companies, and Screened Out tabs. I’ll include applied filters, PitchBook URLs, sector tags, descriptions, consistent formatting, deduplication, and a five-fund sample first so you can approve the structure before the full export. Best regards, George

@carlosd178

Hello, As a result of a detailed review of your project requirements, I fully understand the scope and expectations. I have experience with structured VC/market data extraction, Excel cleanup, and investment database research, and I'm available to start your project right now. I bring deep expertise in PitchBook Research, Data Extraction, Excel, Data Processing, Data Management, Web Search, Data Collection, and deduplication/format validation. One of the key challenges in this project is keeping the PitchBook screen accurate while clearly documenting why each fund was included or screened out. I can apply the filters for North America, Europe, and Asia-Pacific, limit funds to under USD 100M, then organize the workbook into Funds, Portfolio Companies, and Screened Out tabs with clean formatting, live PitchBook URLs, sector tags, and consistent naming. I can also provide the requested five-fund sample first so you can confirm the structure before the full pull is completed. I have a couple of quick questions. • What investment stage and vintage thresholds should be applied once the screen is started? • Do you want healthcare-adjacent funds included only when they have active portfolio companies in healthcare, or based on fund strategy description as well? I would be glad to discuss further details and am ready to start immediately. Looking forward to hearing from you. Best regards, Carlos.

@RubinTh

I have active PitchBook access and experience exporting large, well structured datasets and can complete this data pull accurately. I will run the screen using your four filters, geographic regions fixed to North America, Europe, and Asia Pacific, fund size under USD 100 million, and the stage and vintage thresholds you will confirm, all scoped to healthcare and adjacent verticals including life sciences, digital health, medtech, diagnostics, biotech, and precision medicine. I will deliver an Excel workbook with three tabs: qualifying funds with full PitchBook export fields and applied filters noted, portfolio companies with descriptions, sector tags, and live PitchBook URLs, and a screened out tab noting exclusion reasons. The file will be de-duplicated and consistently formatted throughout. I will provide a five fund sample for your review before completing the full pull. Accuracy is my priority and I will double check names, tags, and URLs before delivery. My rate is negotiable based on final dataset size.

@tonnyKlein

Hello, I’m Dr. Antony—Freelancer.com member since 2014 with 15+ years’ experience and 800+ verified reviews. I can complete your PitchBook data extraction for global healthcare VC managers across North America, Europe, and Asia-Pacific, applying the four required filters: geography, fund size under USD 100M, investment stage, and vintage. I’ll deliver a clean Excel workbook with Funds, Portfolio Companies, and Screened Out tabs, including full export fields, PitchBook URLs, healthcare sector tags, exclusion reasons, and de-duplicated formatting ready for downstream analysis. I can provide the five-fund acceptance sample within 24–48h, then proceed batch by batch for accuracy. You’ll also get a money-back guarantee on originality and quality plus a FREE validation checklist. Should excluded funds be grouped by primary exclusion reason or kept in review order? Let’s create the first milestone to begin. Chat now.

@Hubready

Hello! I am a Florida-based senior software engineer with over 15 years of experience in data processing, web scraping, and data analysis. I carefully read your project description regarding the precise data pull from PitchBook to map the global landscape of venture capital managers, and I am excited about the opportunity to assist you. To ensure I deliver exactly what you need, could you please clarify the following questions to help me better understand the project? 1. What specific data points are you looking to extract from PitchBook? 2. Do you have a preferred format for the final deliverable (e.g., Excel, CSV)? My expertise includes building robust data pipelines and automating data extraction processes, which will be pivotal in achieving your project goals. I have previously worked on projects that involved extracting and managing large datasets, ensuring accuracy and efficiency. I suggest the following tactical steps for success: 1. Define the specific data requirements. 2. Set up a web scraping mechanism to gather the data. 3. Process and analyze the data to ensure it meets your expectations. 4. Deliver the data in your preferred format. I am committed to providing precise results and would love to discuss your project further. Looking forward to your response! - James

@NidaTheExpert

Hello, I’m interested in assisting with your PitchBook data extraction project. I understand the importance of accuracy, clean formatting, and maintaining consistent healthcare-focused screening criteria across large datasets. I can help with: • Running structured PitchBook screens using your required filters • Exporting and organizing VC fund data cleanly into Excel • Building separate tabs for Funds, Portfolio Companies, and Screened Out entities • Deduplicating records and maintaining formatting consistency • Verifying sector relevance, tags, and PitchBook links carefully before delivery I’m comfortable working with large Excel datasets and can provide a 5-fund sample first for validation before completing the full extraction. Best regards, Nida