Talent Database Lead

Summary Every week, 80,000 Hours’s headhunting team searches for people who could fill important roles at organisations working to make transformative AI (TAI) go well , including where TAI intersects with other problems. We use a database of more than 16,000 candidates to find and recommend promising people to hiring managers. Last quarter, hiring managers reached out more than 2,000 times to candidates we suggested, across 187 searches for 79 organisations. Currently, we estimate there’s a one in six chance that the eventual hire for a role is among the candidates we send to the hiring manager. That means we’re often one of the best sources of candidates, and also that we’re still missing many of the people who could be the strongest fit. The biggest constraint is the breadth and quality of our candidate data. Roughly half the people eventually hired for roles we search for were never in our database, rising to closer to two-thirds for our highest-priority searches. And even when the right person is already in our system, we can miss them because we don’t know enough about their experience, strengths, or interests to recognise the fit. We’re hiring a Talent Database Lead to own that problem. Your goal will be to increase the number of high-quality candidates in our database and improve the information that helps us connect them to impactful opportunities. This is a broad, entrepreneurial role. It combines growth, partnerships, ensuring data quality and compliance, and potentially creating new products to gather the data we need. You’ll decide where to focus, test different ways of reaching valuable candidate populations, and build the systems and relationships that lead to ongoing data streams. Location: London or the San Francisco Bay Area preferred; we will also consider remote candidates with overlap in working hours for both PT and CET Salary: Based on experience and location; ranges from £112,000–130,000 (London), $182,000–211,000 (San Francisco Bay Area), $139,000–162,000 (US remote), and £97,000–113,000 (other remote). Deadline: Apply by 11:00 PM BST on August 28, 2026 . Applications will be assessed on a rolling basis, so we recommend applying early. The opportunity We think the ceiling for our headhunting work is much higher than where we are now. Three things are rising in parallel: the number of important roles in AI, the number of people interested in those roles, and the power of LLMs to help match one to the other. Each makes the others more valuable, so progress now is unusually leveraged. We’re already increasing the number and quality of searches we can run. By adding headhunters and using LLMs to search thousands of candidates more efficiently, we completed 51% more searches in Q2 than in Q1 and generated 2.7 times as many candidate reach-outs. Candidate data is now one of the biggest constraints on progressing further. As LLMs improve, we can search more people against more roles while focusing human judgement where it adds the most value — but only if we know about the right people and hold enough information to recognise their fit. Each strong candidate we add to our database, and each improvement in what we know about them, can contribute across a growing number of searches. The role There isn’t yet a fixed playbook. Depending on what you learn, you might work to: Understand demand and prioritise the gaps. Work closely with headhunters and hiring managers to build a live picture of which candidate populations are most needed, where our current coverage is weakest, and which additional information would make those candidates easier to find. Build candidate-acquisition channels. Identify places where promoting 80,000 Hours’s products would reach especially valuable groups, run targeted campaigns, and assess whether they produce candidates who are good fits for top roles. Develop partnerships and data-sharing arrangements. Build relationships with fellowship organisers, training programmes, and other aligned organisations, and create arrangements that are useful, lawful, and consistent with participants’ expectations. Make our products better sources of candidate data. Work with the teams behind advising, the job board, our AI products and other services to identify opportunities to collect useful, shareable candidate information as a natural part of the user experience. Collect better signals, not just more records. Much of what determines whether someone would be an excellent fit is hard to see in a CV or LinkedIn profile: the scope and quality of their work, where they thrive, and which opportunities they would consider. You’ll find responsible ways to build and maintain that richer picture, drawing on candidates and, with appropriate permission, people or programmes that know their work. Set the standard for responsible data use. For every source, we should be able to explain where the information came from, what permission we have to use it, what the person concerned would expect, and how that information moves through our systems. What success looks like in your first 12 months By the end of your first year, we’d expect you to: Have defined a metric that does a good job of tracking the value of new data to the headhunting team. Have launched several data acquisition approaches and developed a clear view of which are worth scaling. Have materially increased the number of high-quality, shareable candidates in the database, particularly in the populations that hiring managers currently struggle most to find. Have improved the quality and completeness of the information we hold in the areas that matter most for matching, such as seniority, interests, and willingness to consider particular kinds of roles. Improved our framework for data provenance, consent, and acceptable use. For any important source, the team should be able to answer: where did this come from, how are we allowed to use this data, and would we be comfortable explaining that use to the person concerned? Who this role is for You’ll enjoy this work and do it well if you: Take ownership of ambiguous problems. You’ve run something where nobody handed you the steps: a project, function, product, programme, or company. You’re enough of a generalist to make things happen as a team of one. Build trust and work through other people. Much of the role involves collaborating with headhunters, hiring managers, product teams, and external organisations. You listen carefully, communicate clearly, and can move a project forward even when you don’t directly manage the people involved. Make good bets with incomplete information. You can estimate the likely value of an opportunity without needing perfect data, design a cheap way to test it, and change direction when the results differ from what you expected. Move comfortably between strategy and execution. You’re as willing to work out which candidate population matters most as you are to draft a partnership proposal, run user interviews, or personally test an early approach. Care about the people behind the records. You don’t treat compliance or consent as someone else’s problem. You notice when a proposed use of data might conflict with what a person reasonably expects, and you look for ways to achieve a goal without sacrificing trust. Understand the field well enough to prioritise within it. You have a good understanding of effective altruism principles and the ecosystem of people working to make AI go well, including which organisations, roles, and candidate populations are likely to matter most. You’re able and willing to deepen that understanding through independent learning and conversations with specialists. We don’t expect you to be a data scientist or engineer. We do expect you to be comfortable using data to diagnose bottlenecks and evaluate results, discussing how information enters and moves through a system, and learning enough technical detail to make sound decisions. It’s a plus, but not a requirement, if you: Have experience in growth, partnerships, business development, or recruiting operations. Have worked with CRMs, candidate databases, product data, or data pipelines. Have existing networks in AI safety, policy, technical research, or adjacent ecosystems. We don’t expect any one person to be equally strong in every dimension, and we encourage you to apply even if you don’t meet every criterion. How you’ll work This role sits within the career services team alongside headhunting, advising, the job board, and our AI products. The subteams share information about what they’re seeing across the ecosystem and regularly help one another with overlapping problems. You’ll work particularly closely with the headhunting team. That creates a feedback loop: search by search, you’ll be able to see whether the candidates and information you’re bringing into the database are turning into strong leads, interviews, and eventual placements. You’ll also work with product teams across 80,000 Hours and with external organisations that could become important sources of candidates or information. The function is still taking shape, so you’ll have substantial influence over how the work is prioritised and how it operates. You’ll report to the director of the career services team and work closely with the wider career services programme as well as colleagues across 80,000 Hours. This is a full-time role. The start date is flexible, though we’d like the person we hire to start as soon as possible. Salary and Benefits Salaries at 80,000 Hours are set using a salary calculator that is visible to all staff and accounts for the specific role, location, and candidate's experience. For this role, we expect salary to range from £112,000–130,000 (London), $182,000–211,000 (San Francisco Bay Area), $139,000–162,000 (US remote), and £97,000–113,000 (other remote). We can support both UK and US visa sponsorship, but we cannot guarantee US visa applications will be successful. You can read more about the US visa types we can sponsor here . Our benefits include: 25 days of paid holiday, plus public holidays Private medical insurance Long-term disability insurance Pension scheme / retirement plan with employer contributions Up to 14 weeks of fully paid parental leave and childcare allowance for children under five £5,000 annual mental health support allowance £5,000 annual self-development budget The option to use 10% of your time for self-development Gym, shower facilities, and unlimited free food at our London office How to Apply Apply by 11:00 PM BST on August 28, 2026 . We'll review applications as they come in and begin assessing candidates as soon as some have met the bar. We reserve the right to close applications before the stated deadline. The process is likely to include interviews, work tests, and a multi-day assessment (preferably in person). We pay for work tests and the multi-day assessment, conditional on location and right to work in the country where you take the assessment. We know factors like gender, race, and socioeconomic background can affect people's willingness to apply for roles where they meet many but not all the suggested attributes. We especially encourage people from underrepresented backgrounds to apply, even if you don't meet every criterion.