Qureos Mentor

Anthropic

<div><div><h2 class="jobSectionHeader"><b>About Anthropic</b></h2>
<p>
Anthropic&rsquo;s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.</p></div><div><h2 class="jobSectionHeader"><b>
About the role</b></h2>
<p>
The Research Data Platform team builds the tools that Anthropic's researchers use every day to manage, query, and analyze the data that goes into training and evaluating frontier models. We power the internal applications researchers rely on to monitor RL runs, explore finetuning datasets, and understand what's happening inside their experiments.</p>
<p>
We're looking for engineers who love working directly with users and who excel at building data products &mdash; the pipelines that move data out of training runs into queryable storage, and the APIs, libraries, and services researchers use to manage and explore it. This role sits closer to the research workflow than a typical data infrastructure position: you'll often embed with research teams, build ML-specific tooling alongside them, and leverage what our Data Infrastructure team has already built rather than reinventing it.</p>
<p>
We do not require prior ML or AI training experience. If you enjoy working closely with technical users, learning new domains quickly, and building tools people actually want to use, you'll pick up the research context fast.</p>
<h2 class="jobSectionHeader"><b>
Responsibilities</b></h2>
<ul><li>Build and operate data pipelines that extract data from research training runs and land it in storage systems that are easy and fast to query</li>
<li>Work closely with researchers to design and build APIs, libraries, and web interfaces that support data management, exploration, and analysis</li>
<li>Develop dataset management, data cataloging, and provenance tooling that researchers use in their day-to-day work</li>
<li>Embed with research teams to understand their workflows, identify high-leverage tooling opportunities, and ship solutions quickly</li>
<li>Collaborate with adjacent teams to build on existing systems rather than reinventing them</li>
</ul><h2 class="jobSectionHeader"><b>You may be a good fit if you</b></h2>
<ul><li>Have significant software engineering experience, particularly building data-intensive applications or internal tooling</li>
<li>Enjoy working directly with users, gathering requirements iteratively, and shipping things that get adopted</li>
<li>Are results-oriented, with a bias towards flexibility and impact</li>
<li>Pick up slack, even if it goes outside your job description</li>
<li>Want to learn more about machine learning research</li>
<li>Care about the societal impacts of your work</li>
</ul><h2 class="jobSectionHeader"><b>Strong candidates may also have experience with</b></h2>
<ul><li>Large-scale ETL, columnar storage formats, and query engines (e.g., Spark, BigQuery, DuckDB, Parquet)</li>
<li>High-volume time series data &mdash; ingestion, storage, and efficient querying</li>
<li>Data cataloging, lineage, or metadata management systems</li>
<li>ML experiment tracking or metrics platforms</li>
<li>Working in environments where engineers partner closely with quantitative users &mdash; research labs, trading firms, observability or analytics startups</li>
<li>Complex data visualization and full-stack web application development</li>
</ul></div><div><div><div><div><p>
The annual compensation range for this role is listed below.</p>
<p>
For sales roles, the range provided is the role&rsquo;s On Target Earnings (&quot;OTE&quot;) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.</p></div></div><p>
Annual Salary:</p><p>
$320,000 - $405,000 USD</p></div></div><div><h2 class="jobSectionHeader"><b>
Logistics</b></h2>
<p><b>
Minimum education: </b>Bachelor&rsquo;s degree or an equivalent combination of education, training, and/or experience</p>
<p><b>
Required field of study: </b>A field relevant to the role as demonstrated through coursework, training, or professional experience</p>
<p><b>
Minimum years of experience: </b>Years of experience required will correlate with the internal job level requirements for the position</p>
<p><b>
Location-based hybrid policy:</b> Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.</p>
<p><b>
Visa sponsorship:</b> We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.</p>
<p><b>
We encourage you to apply even if you do not believe you meet every single qualification.</b> Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.<br>
<br>
<b>Your safety matters to us.</b> To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links&mdash;visit anthropic.com/careers directly for confirmed position openings.</p>
<h2 class="jobSectionHeader"><b>
How we're different</b></h2>
<p>
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact &mdash; advancing our long-term goals of steerable, trustworthy AI &mdash; rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.</p>
<p>
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.</p>
<h2 class="jobSectionHeader"><b>
Come work with us!</b></h2>
<p>
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. <b>Guidance on Candidates' AI Usage:</b> Learn about our policy for using AI in our application process.</p></div></div>

Software Engineer, Research Data Platform

<div><div><h2 class="jobSectionHeader"><b>About Anthropic</b></h2>
<p>
Anthropic&rsquo;s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.</p></div><div><h2 class="jobSectionHeader"><b>
About the role</b></h2>
<p>
Anthropic's RL Scaling Science team studies how reinforcement learning behaves as we scale it (across model size, compute, and task horizon) and turns that understanding into the training recipes behind our frontier models. As a Research Engineer on this team, you'll design and run large-scale experiments to understand and resolve bottlenecks, build the benchmarks that make long-horizon progress measurable, and ship validated findings directly into production training.</p>
<p>
This role lives at the boundary between research and engineering. The problems are open, the experiments run at frontier scale, and the path from a robust result to production is short.</p>
<h2 class="jobSectionHeader"><b>
Key responsibilities</b></h2>
<ul><li>Design, run, and interpret large-scale RL experiments, reasoning rigorously about what the data does and doesn't show</li>
<li>Investigate how RL improves as horizon, compute, and model size grow</li>
<li>Build and maintain benchmarks for long-horizon RL so progress is measurable and reproducible</li>
<li>Translate validated findings into production training recipes, exercising judgment about when a result is robust enough to ship</li>
<li>Debug complex issues at the seam where research meets infrastructure - failures that only appear at scale</li>
<li>Partner closely with adjacent RL teams across research and engineering and advance our overall RL stack</li>
</ul><h2 class="jobSectionHeader"><b>Minimum qualifications</b></h2>
<ul><li>Strong empirical research skills in Reinforcement Learning, large-scale ML training, or a closely adjacent area</li>
<li>Demonstrated ability to own large experiments end-to-end, from design through interpretation</li>
<li>Proficiency in Python and experience working with large-scale or distributed ML systems</li>
<li>Comfort operating at the research/systems boundary, including debugging where the two meet</li>
<li>Care about the societal impacts of AI and responsible scaling</li>
</ul><h2 class="jobSectionHeader"><b>Preferred qualifications</b></h2>
<ul><li>Published or shipped work in long-horizon RL or RL fundamentals</li>
<li>Experience translating research findings into production training recipes</li>
<li>Demonstrated large scale industry impact via RL interventions</li>
<li>Experience working on frontier-scale training runs with long trajectories</li>
</ul><h2 class="jobSectionHeader"><b>Representative projects</b></h2>
<ul><li>Design a benchmark suite for long-horizon RL that distinguishes genuine capability gains from artifacts of evaluation setup</li>
<li>Take a promising experimental finding, stress-test it across model scales, and work with training teams to land it in a production recipe</li>
<li>Investigate an unexpected scaling trend in an RL run and trace it to a root cause spanning algorithm, data, and infrastructure</li></ul></div><p></p><div><div><div><div><p><br>
The annual compensation range for this role is listed below.</p>
<p>
For sales roles, the range provided is the role&rsquo;s On Target Earnings (&quot;OTE&quot;) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.</p></div></div><p>
Annual Salary:</p><p>
&pound;375,000 - &pound;640,000 GBP</p></div></div><div><h2 class="jobSectionHeader"><b>
Logistics</b></h2>
<p><b>
Minimum education: </b>Bachelor&rsquo;s degree or an equivalent combination of education, training, and/or experience</p>
<p><b>
Required field of study: </b>A field relevant to the role as demonstrated through coursework, training, or professional experience</p>
<p><b>
Minimum years of experience: </b>Years of experience required will correlate with the internal job level requirements for the position</p>
<p><b>
Location-based hybrid policy:</b> Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.</p>
<p><b>
Visa sponsorship:</b> We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.</p>
<p><b>
We encourage you to apply even if you do not believe you meet every single qualification.</b> Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.<br>
<br>
<b>Your safety matters to us.</b> To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links&mdash;visit anthropic.com/careers directly for confirmed position openings.</p>
<h2 class="jobSectionHeader"><b>
How we're different</b></h2>
<p>
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact &mdash; advancing our long-term goals of steerable, trustworthy AI &mdash; rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.</p>
<p>
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.</p>
<h2 class="jobSectionHeader"><b>
Come work with us!</b></h2>
<p>
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. <b>Guidance on Candidates' AI Usage:</b> Learn about our policy for using AI in our application process.</p></div></div>

Research Engineer, RL Scaling Science

<div><div><h2 class="jobSectionHeader"><b>About Anthropic</b></h2>
<p>
Anthropic&rsquo;s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.</p></div><div><h2 class="jobSectionHeader"><b>
About the role</b></h2>
<p>
The Domain Scaling team has the goal to make Claude world-class at real-world knowledge work in domains like finance, healthcare, and legal. This is a unique role that combines executing directly on applied research and data sourcing (real-world and synthetic) to improve our models. You'll own the end-to-end process of creating RL environments for new capabilities: identifying high-value tasks, designing reward signals, managing vendor relationships, and measuring impact on model performance.</p>
<h2 class="jobSectionHeader"><b>
Responsibilities</b></h2>
<ul>
<li><p>Own the data strategy for knowledge work verticals end-to-end, from task sourcing through RL training</p>
</li>
<li><p>Manage technical relationships with external data vendors, including evaluation of data quality and reward design</p>
</li>
<li><p>Collaborate with domain experts to design data pipelines and evaluations</p>
</li>
<li><p>Explore novel ways of creating RL envs for high value tasks</p>
</li>
<li><p>Develop and improve QA frameworks to catch reward hacking and ensure env quality</p>
</li>
<li><p>Run generalization experiments to measure how data strategy changes improve model capabilities</p>
</li>
<li><p>Partner with other RL research teams and product teams to translate capability goals into training envs and evals</p>
</li>
</ul><h2 class="jobSectionHeader"><b>You may be a good fit if you</b></h2>
<ul>
<li><p>Have experience with fine-tuning large language models for specific domains or real-world use cases</p>
</li>
<li><p>Have experience with reinforcement learning, reward design, or training data curation for LLMs</p>
</li>
<li><p>Are comfortable managing technical vendor relationships and iterating quickly on feedback</p>
</li>
<li><p>Find value in reading through datasets to understand them and spot issues</p>
</li>
<li><p>Have strong cross-functional collaboration skills</p>
</li>
<li><p>Are passionate about making AI more useful and accessible across different industries</p>
</li>
<li><p>Are excited about a role that includes a combination of applied research and hands-on data work</p>
</li>
</ul><h2 class="jobSectionHeader"><b>Strong candidates may also</b></h2>
<ul>
<li><p>Have experience training production ML systems</p>
</li>
<li><p>Have experience designing evals or benchmarks for LLMs</p>
</li>
<li><p>Have domain expertise in a vertical where we would like to make our models more useful</p>
</li>
<li><p>Have experience working with external vendors or technical partners</p>
</li>
</ul></div><div><div><div><div><p>The annual compensation range for this role is listed below.</p>
<p>
For sales roles, the range provided is the role&rsquo;s On Target Earnings (&quot;OTE&quot;) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.</p></div></div><p>
Annual Salary:</p><p>
$350,000 - $850,000 USD</p></div></div><div><h2 class="jobSectionHeader"><b>
Logistics</b></h2>
<p><b>
Minimum education: </b>Bachelor&rsquo;s degree or an equivalent combination of education, training, and/or experience</p>
<p><b>
Required field of study: </b>A field relevant to the role as demonstrated through coursework, training, or professional experience</p>
<p><b>
Minimum years of experience: </b>Years of experience required will correlate with the internal job level requirements for the position</p>
<p><b>
Location-based hybrid policy:</b> Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.</p>
<p><b>
Visa sponsorship:</b> We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.</p>
<p><b>
We encourage you to apply even if you do not believe you meet every single qualification.</b> Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.<br>
<br>
<b>Your safety matters to us.</b> To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links&mdash;visit anthropic.com/careers directly for confirmed position openings.</p>
<h2 class="jobSectionHeader"><b>
How we're different</b></h2>
<p>
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact &mdash; advancing our long-term goals of steerable, trustworthy AI &mdash; rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.</p>
<p>
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.</p>
<h2 class="jobSectionHeader"><b>
Come work with us!</b></h2>
<p>
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. <b>Guidance on Candidates' AI Usage:</b> Learn about our policy for using AI in our application process.</p></div></div>

Research Engineer, Domain Scaling

<div><div><h2 class="jobSectionHeader"><b>About Anthropic</b></h2>
<p>
Anthropic&rsquo;s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.</p></div><div><h2 class="jobSectionHeader"><b>
About the role</b></h2>
<p>
We are seeking a Recruiting Research Scientist to join our People Data Solutions team. You&rsquo;ll be the research expert supporting our Recruiting organization, using rigorous scientific methods to advance our understanding of recruiting funnels, interview effectiveness, candidate experience, and recruiting capacity. This role sits at the intersection of organizational science, behavioral research, and people strategy &ndash; developing novel frameworks and conducting systematic research that drives evidence-based people decisions across our growing organization.</p>
<p>
This role offers the opportunity to make a significant impact on both our recruiting practices and the broader field of people science at a leading AI safety company.</p>
<h2 class="jobSectionHeader"><b>
Responsibilities</b></h2>
<p><b>
Research design &amp; scientific inquiry</b></p>
<ul>
<li><p>Design and execute systematic research studies to answer fundamental questions about recruiting funnel health, assessment quality, candidate experience, and quality of hire</p>
</li>
<li><p>Generate and test hypotheses about sourcing strategies, interview design, and selection decisions using rigorous experimental and quasi-experimental methods</p>
</li>
<li><p>Conduct mixed-method research to understand what are the drivers and blockers to recruiting operations.</p>
</li>
<li><p>Navigate research ethics considerations when studying candidate data, ensuring responsible research practices</p>
</li>
</ul><p><b>Selection &amp; assessment research</b></p>
<ul>
<li><p>Design and execute validation studies to assess the quality of interviews and other selection tools</p>
</li>
<li><p>Utilize psychometric techniques to analyze and improve interviewer calibration and rating consistency</p>
</li>
<li><p>Lead investigative research into innovative approaches for candidate assessment</p>
</li>
</ul><p><b>Metrics design and governance</b></p>
<ul>
<li><p>Design the metrics framework for recruiting org health &mdash; defining the canonical KPIs, dimensions, and definitions that leadership uses to understand funnel performance, capacity, and hiring quality</p>
</li>
<li><p>Establish the governance and definitional rigor that keeps metrics consistent across tools and reporting surfaces</p>
</li>
</ul><p><b>Analytical solution building</b></p>
<ul>
<li><p>Architect analytical solutions that convert research insights into actionable products, empowering stakeholders to execute data-driven scenario and strategic planning</p>
</li>
<li><p>Quantify the adoption and downstream impact of deployed tools, driving iterative improvements</p>
</li>
</ul><p><b>Visualization &amp; communication</b></p>
<ul>
<li><p>Build compelling visualizations and dashboards that make complex research findings accessible to diverse audiences</p>
</li>
<li><p>Present research findings to senior leadership with clear, actionable recommendations</p>
</li>
</ul><h2 class="jobSectionHeader"><b>Minimum Qualifications:</b></h2>
<ul>
<li><p>Hold an advanced degree (Master&rsquo;s or PhD) in I/O Psychology, Organizational Behavior, Statistics, Data Science, Economics, Behavioral Science, or a related research field</p>
</li>
<li><p>Have experience with selection research, assessment validation, psychometrics, or recruiting funnel analytics</p>
</li>
<li><p>Are comfortable working in the People Analytics tech stack and collaborating with data engineers</p>
</li>
<li><p>Are proficient in SQL and Python/R, with experience in statistical analysis and machine learning</p>
</li>
<li><p>Have experience with data visualization and can tell compelling stories with research findings</p>
</li>
<li><p>Possess excellent communication skills and can influence stakeholders at all levels</p>
</li>
<li><p>Thrive in ambiguity and can balance rigor with pragmatism</p>
</li>
<li><p>Have a track record of challenging assumptions with data and changing long-held practices</p>
</li>
<li><p>Can navigate sensitive topics diplomatically while maintaining analytical rigor</p>
</li>
<li><p>Demonstrate intellectual humility and comfort with iterative discovery</p>
</li>
<li><p>Use data to improve how organizations find, assess, and hire talent</p>
</li>
</ul><h2 class="jobSectionHeader"><b>Preferred Qualifications:</b></h2>
<ul>
<li><p>5 + years of experience in research, people analytics, or related quantitative fields with demonstrated research methodology expertise</p>
</li>
<li><p>Background in recruiting analytics specifically (not just general analytics)</p>
</li>
<li><p>Experience running interview or assessment validation studies</p>
</li>
<li><p>Experience building self-service analytics tools or dashboards</p>
</li>
<li><p>Previous experience in high-growth technology companies or AI/ML organizations</p>
</li>
<li><p>Familiarity with network analysis, machine learning, or advanced statistical methods</p>
</li>
<li><p>Experience with BigQuery and modern data stack tools</p>
</li>
<li><p>Experience with Greenhouse, Gem, ModernLoop, or similar recruiting tools</p>
</li>
</ul></div><div><div><div><div><p>The annual compensation range for this role is listed below.</p>
<p>
For sales roles, the range provided is the role&rsquo;s On Target Earnings (&quot;OTE&quot;) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.</p></div></div><div><b>
Annual Salary:</b></div><div>
$275,000 - $370,000 USD</div></div></div><div><h2 class="jobSectionHeader"><b>
Logistics</b></h2>
<p><b>
Minimum education: </b>Bachelor&rsquo;s degree or an equivalent combination of education, training, and/or experience</p>
<p><b>
Required field of study: </b>A field relevant to the role as demonstrated through coursework, training, or professional experience</p>
<p><b>
Minimum years of experience: </b>Years of experience required will correlate with the internal job level requirements for the position</p>
<p><b>
Location-based hybrid policy:</b> Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.</p>
<p><b>
Visa sponsorship:</b> We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.</p>
<p><b>
We encourage you to apply even if you do not believe you meet every single qualification.</b> Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.<br>
<br>
<b>Your safety matters to us.</b> To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links&mdash;visit anthropic.com/careers directly for confirmed position openings.</p>
<h2 class="jobSectionHeader"><b>
How we're different</b></h2>
<p>
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact &mdash; advancing our long-term goals of steerable, trustworthy AI &mdash; rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.</p>
<p>
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.</p>
<h2 class="jobSectionHeader"><b>
Come work with us!</b></h2>
<p>
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. <b>Guidance on Candidates' AI Usage:</b> Learn about our policy for using AI in our application process.</p></div></div>

People Research Scientist, Recruiting

<div><div><h2 class="jobSectionHeader"><b>About Anthropic</b></h2>
<p>
Anthropic&rsquo;s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.</p></div><div><h2 class="jobSectionHeader"><b>
About the role</b></h2>
<p>
As an early member of our Finance Analytics and Business Intelligence team, you will play an instrumental role in our company's mission of building safe and beneficial artificial intelligence by delivering the analysis and analytics infrastructure that shape how Finance &amp; Strategy (F&amp;S) understands Anthropic's business. In this unique company, technology, and moment in history, your work will directly inform how leadership navigates one of the fastest-growing businesses in the world.</p>
<p>
This is a role spanning data analysis, business intelligence and analytics engineering, partnering closely across several cross functional teams including Data Engineering, Data Science &amp; Analytics, and Finance &amp; Strategy. You will produce high-impact, high-visibility analyses that answer leadership's most pressing questions about the financial trajectory of the business&mdash;revenue drivers, margin dynamics, compute economics, customer segments, and the forces shaping our P&amp;L. You'll also build the datasets, pipelines, and BI foundations that make those insights possible at scale and ensure every number the executive team sees is one they can trust. You've worked in cultures of excellence in the past and are eager to apply that experience to both the craft of analysis and the rigor of building durable data systems as our company goes through a phase of rapid growth.</p>
<h2 class="jobSectionHeader"><b>
Responsibilities:</b></h2>
<ul>
<li><p>Deliver high-impact analyses and deep dives that surface key insights about Anthropic's financial performance directly to finance and executive leadership</p>
</li>
<li><p>Build and maintain canonical datasets, dashboards, and scaled reporting solutions that provide real-time financial visibility across the company</p>
</li>
<li><p>Partner with Finance &amp; Strategy teams (Product, Compute, GTM, and Corporate) to answer their most important questions and streamline recurring analytical workflows</p>
</li>
<li><p>Establish analytics engineering and BI best practices for F&amp;S, including data management, governance, and reporting standards</p>
</li>
<li><p>Partner with Data Infrastructure, Analytics Engineering, and Financial Systems teams to develop scalable data pipelines supporting finance and accounting analytics</p>
</li>
<li><p>Champion data-informed decision making across the organization</p>
</li>
</ul><h2 class="jobSectionHeader"><b>You may be a good fit if you:</b></h2>
<ul>
<li><p>Have 6+ years of hands-on experience spanning data analysis, business intelligence, and/or analytics engineering, ideally with exposure to Finance &amp; Strategy, Data Infrastructure and Analytics Engineering</p>
</li>
<li><p>Are highly proficient in SQL and Python for analysis, data manipulation, ETL/ELT, and automation</p>
</li>
<li><p>Have a track record of producing analyses that have meaningfully influenced business or leadership decisions</p>
</li>
<li><p>Have extensive experience with data visualization and using Claude / AI tools for data analysis and BI</p>
</li>
<li><p>Have experience with cloud platforms (AWS, GCP) and modern data stack tools (dbt, Airflow, etc.)</p>
</li>
<li><p>Have hands-on experience working with financial systems and building downstream data models from these systems</p>
</li>
<li><p>Excel at translating complex business questions into both sharp analyses and durable technical solutions, and can communicate effectively with technical and non-technical stakeholders, including executives</p>
</li>
<li><p>Are detail-oriented with a deep commitment to data accuracy</p>
</li>
<li><p>Thrive in fast-paced environments, can manage multiple priorities while maintaining high-quality deliverables</p>
</li>
<li><p>Operate with an ownership mindset, taking projects end-to-end from ambiguous question to trusted answer and seeing them through to impact</p>
</li>
</ul><h2 class="jobSectionHeader"><b>Strong candidates may have:</b></h2>
<ul>
<li><p>Championed AI driven analytics and financial analysis within their organizations</p>
</li>
<li><p>Prior experience in high-growth technology companies or startups</p>
</li>
<li><p>Strong financial acumen with deep understanding of finance principles</p>
</li>
<li><p>Knowledge of statistical analysis and advanced analytics techniques</p>
</li>
<li><p>Familiarity with data governance best practices and experience implementing data quality frameworks</p>
</li>
</ul></div><div><div><div><div><p>The annual compensation range for this role is listed below.</p>
<p>
For sales roles, the range provided is the role&rsquo;s On Target Earnings (&quot;OTE&quot;) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.</p></div></div><div><b>
Annual Salary:</b></div><div>
$270,000 - $320,000 USD</div></div></div><div><h2 class="jobSectionHeader"><b>
Logistics</b></h2>
<p><b>
Minimum education: </b>Bachelor&rsquo;s degree or an equivalent combination of education, training, and/or experience</p>
<p><b>
Required field of study: </b>A field relevant to the role as demonstrated through coursework, training, or professional experience</p>
<p><b>
Minimum years of experience: </b>Years of experience required will correlate with the internal job level requirements for the position</p>
<p><b>
Location-based hybrid policy:</b> Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.</p>
<p><b>
Visa sponsorship:</b> We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.</p>
<p><b>
We encourage you to apply even if you do not believe you meet every single qualification.</b> Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.<br>
<br>
<b>Your safety matters to us.</b> To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links&mdash;visit anthropic.com/careers directly for confirmed position openings.</p>
<h2 class="jobSectionHeader"><b>
How we're different</b></h2>
<p>
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact &mdash; advancing our long-term goals of steerable, trustworthy AI &mdash; rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.</p>
<p>
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.</p>
<h2 class="jobSectionHeader"><b>
Come work with us!</b></h2>
<p>
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. <b>Guidance on Candidates' AI Usage:</b> Learn about our policy for using AI in our application process</p></div></div>

Analytics, Finance & StrategyNew