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ai research scientist

Handshake

<div>
 
 About Handshake
 
 
 
 Handshake is the career network for the AI economy. 20 million knowledge workers, 1,600 educational institutions, 1 million employers (including 100% of the Fortune 50), and every foundational AI lab trust Handshake to power career discovery, hiring, and upskilling, from freelance AI training gigs to first internships to full-time careers and beyond. This unique value is leading to unparalleled growth; in 2025, we tripled our ARR at scale.
 
 
 
 Why Join Handshake Now
 
 
 
 <ul>
 <li>
 Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feel
 </li>
 <li>
 Work hand-in-hand with world-class AI labs, Fortune 500 partners and the world&rsquo;s top educational institutions
 </li>
 <li>
 Join a team with leadership from Scale AI, Meta, xAI, Notion, Coinbase, and Palantir, among others
 </li>
 <li>
 Build a massive, fast-growing business with billions in revenue
 
 
 </li>
 </ul>
 
 About The Role
 
 
 
 Untangling the science of Data &amp; Evaluations for Frontier AI
 
 
 Thanks to our massive network of the world&rsquo;s top experts in all domains, the demand for human data from Handshake AI has exploded (with revenue growing from 0 to well over 9-figures in the first year and growth only accelerating since). Now the world&rsquo;s top AI Labs are looking to Handshake for advice on how to leverage human expertise to make frontier models more useful for everyone, and we are forming a leading research group to advance the science of Data and Evaluations for AI.
 
 
 
 You Will
 
 
 
 <ul>
 <li>
 Publish papers, open source software, and do bleeding-edge open science on AI agents, LLMs and frontier multimodal models, RL environments, post-training.
 </li>
 <li>
 Work with all of the top AI Labs in the world and understand/shape what their researchers are prioritizing (uniquely, you get to work on research at a company whose customers are top AI researchers)
 </li>
 <li>
 Create public benchmarks that meaningfully measure AI progress, leveraging thousands of the world&rsquo;s top experts in different domains from the Handshake network to construct the most representative/high-quality benchmark.
 </li>
 <li>
 Shape the frontier of AI through high-impact research on topics that matter: how to measure/value data, how to effectively evaluate AI, what shapes of data are most effective as AI advances, what makes effective training/RL environments, post-training data recipes.
 
 
 </li>
 </ul>
 
 Desired Capabilities
 
 
 
 <ul>
 <li>
 Based in San Francisco, and excited to work in the office.
 </li>
 <li>
 Ph.D. in ML/AI, data science, or related fields.
 </li>
 <li>
 Publications in top AI/ML venues like NeurIPS, ICML, ICLR.
 </li>
 <li>
 Builders who love to tinker with LLMs/Agents and ship high-quality software, benchmarks/datasets, research, blogs.
 
 
 </li>
 </ul>
 
 Perks
 
 
 
 Handshake delivers benefits that help you feel supported&mdash;and thrive at work and in life.
 
 
 
 
 The below benefits are for full-time US employees.
 
 
 
 
 🎯
 
 Ownership:
 
 Equity in a fast-growing company
 
 
 💰
 
 Financial Wellness
 
 : 401(k) match, competitive compensation, financial coaching
 
 
 🍼
 
 Family Support:
 
 Paid parental leave, fertility benefits, parental coaching
 
 
 💝
 
 Wellbeing:
 
 Medical, dental, and vision, mental health support, $500 wellness stipend
 
 
 📚
 
 Growth:
 
 $2,000 learning stipend, ongoing development
 
 
 💻
 
 Remote &amp; Office:
 
 Internet, commuting, and free lunch/gym in our SF office
 
 
 🏝
 
 Time Off:
 
 Flexible PTO, 15 holidays + 2 flex days, winter #ShakeBreak where our whole office closes for a week!
 
 
 🤝
 
 Connection:
 
 Team outings &amp; referral bonuses
 
 
 Explore our mission, values, and comprehensive US benefits at joinhandshake.com/careers.
 
 
 Compensation Range: $320K - $365K
 
 
</div>

AI Research Scientist

Google

<div>
 Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.
 
 
 Note: By applying to this position you will have an opportunity to share your preferred working location from the following:
 
 San Francisco, CA, USA; Reston, VA, USA
 
 .
 
 Minimum qualifications:
 
 
 
 <ul>
 <li>
 Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
 </li>
 <li>
 3 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.
 
 
 </li>
 </ul>
 
 Preferred qualifications:
 
 
 
 <ul>
 <li>
 3 years of experience developing and deploying machine learning and AI models in production settings.
 </li>
 <li>
 Experience at the intersection of security or fraud and ML.
 </li>
 <li>
 Experience applying a variety of unsupervised, semi-supervised, and supervised machine learning techniques, and the ability to turn big data into actionable intelligence.
 </li>
 <li>
 Experience building LLM-powered applications to automate the analysis and contextualization of complex data.
 </li>
 <li>
 Experience with the challenges in applying machine learning in a non-stationary and adversarial environment.
 </li>
 <li>
 Ability to evaluate, analyze, and improve machine learning models and LLM-driven systems.
 
 
 </li>
 </ul>
 
 About The Job
 
 
 
 The Google Cloud Gusto AI Data Science Research team develops innovative, data-driven solutions to today&rsquo;s most challenging cybersecurity problems. By leveraging data derived from Google's unparalleled view of the threat landscape, our cross-functional, applied research team experiments and delivers impactful findings for both our customers and the broader cybersecurity industry.
 
 
 We are looking for a Research Data Scientist to help us solve challenging cybersecurity problems and protect billions of customers by applying their expert knowledge of machine learning, statistics, and Generative AI. In this role, you will partner with subject matter experts on the front lines defending against advanced threat actors, iteratively develop new capabilities, and work closely with our engineering team to deploy and maintain them. Our team works on a wide variety of cybersecurity challenges including agentic security operations, threat intelligence contextualization, security-tuning LLMs, dark web threat detection, and more. We encourage sharing impactful learnings through publications at academic conferences and talks at industry venues.
 
 
 The US base salary range for this full-time position is $147,000-$211,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
 
 
 Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google .
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Explore promising areas of future research at the intersection of cybersecurity and machine learning.
 </li>
 <li>
 Drive the research and development of new models and analytic products to solve cybersecurity problems.
 </li>
 <li>
 Develop models and analytics. Move from proof of concept to minimum viable product quickly and efficiently.
 </li>
 <li>
 Work closely with other engineering teams to develop scalable data pipelines, deploy models/analytics, and enact telemetry-driven model improvements over time.
 </li>
 <li>
 Communicate research results to stakeholders and the research community through documentation, white papers, peer-reviewed publications, and presentations.
 
 
 
 </li>
 </ul>
 Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .
</div>

Research Data Scientist, Cybersecurity, Google Cloud

Autopoiesis Sciences

<div>
 
 
 About The Role
 
 
 
 
 
 
 Autopoiesis Sciences is a San Francisco-based AI lab building systems that can do science autonomously. We are building the architectures, training methods, and reasoning systems that give AI the judgment to pursue discovery on its own, working the full stack from how scientific reasoning is distilled into models to how the research process itself can be made autonomous. We are backed by Informed Ventures, Alpaca VC, and VitalStage Ventures, Adam Grosser, Ally Warson, Hiro Mizushima, Mike Mahklow, Cross Atlantic Angels, and others.
 
 
 
 
 
 We are currently testing a newly trained autonomous AI system across a broad range of real-world tasks and need sharp, curious people to help us do it. Our AI reasons and plans autonomously, then relays instructions to a human operator who executes them across whatever interface the task requires. For the purposes of this research, it is the most direct way to study unconstrained autonomous behavior at the fidelity we need. You are the hands. The AI is the brain. Together, you close the loop.
 
 
 
 
 
 
 What You'll Be Doing
 
 
 
 
 
 <ul>
 <li>
 Receiving real-time instructions from an autonomous AI system and executing them accurately across whatever interface the task requires
 </li>
 <li>
 Logging outcomes, flagging ambiguities, and providing structured feedback that feeds directly into our research
 </li>
 <li>
 Working alongside ML researchers and engineers to help refine evaluation protocols as the project evolves
 </li>
 <li>
 Participating in debrief sessions where your observations shape how we understand and improve the system
 </li>
 <li>
 Occasionally supporting broader lab operations and research workflows as needed
 </li>
 </ul>
 
 
 
 
 
 Who We're Looking For
 
 
 
 
 
 <ul>
 <li>
 Curious about AI research and autonomous systems, whether through coursework, personal interest, or prior experience
 </li>
 <li>
 No degree required, but a background or active interest in STEM is a plus
 </li>
 <li>
 Comfortable following precise technical instructions quickly and accurately
 </li>
 <li>
 Detail-oriented enough to notice when something unexpected happens and articulate it clearly
 </li>
 <li>
 Interested in how autonomous AI systems actually behave outside of demos and papers
 </li>
 <li>
 Reliable, communicative, and able to work on-site at our SF office and warehouse space
 </li>
 </ul>
 
 
 
 
 
 Compensation and Benefits
 
 
 
 
 
 <ul>
 <li>
 Duration: 3 months with potential for extension
 </li>
 <li>
 Mentorship from researchers and engineers working on autonomous AI systems
 </li>
 <li>
 Collaborate in building a thoughtful, mission-driven team culture focused on autonomous scientific discovery
 </li>
 <li>
 Compensation packages are variable based on experience, expertise, and contribution potential. If your expectations fall outside our stated range, we encourage you to apply regardless. The range for this role is $25/hr-35/hr
 </li>
 </ul>
 
 
 
 
 
 Get To Know Us
 
 
 
 
 
 
 We're a dedicated team of scientists, researchers, and engineers who believe deeply in the transformative potential of our work. You'll work closely with our leadership team including Chief Executive Officer Joseph Reth (Attended University for CS at 14, former DARPA), Chief Business Officer Dr. Eike Gerhardt (University of T&uuml;bingen PhD, University of T&uuml;bingen staff), Chief Scientist Dr. Larry Callahan (University of Chicago PhD, former FDA, former NIH), and VP of Research Vincent Karpf (UC Berkeley).
 
 
 
 
 
 
 Application Process:
 
 Due to the high volume of automated applications, we only accept applications through LinkedIn as it helps us connect with genuine candidates. We have systems in place to detect automated submissions and strongly advise against using bots or automated tools in your application process. Please be human in your approach.
 
 
 
 
 
 
 Equal Opportunity:
 
 Autopoiesis Sciences, Inc. is an equal opportunity employer committed to diversity and inclusion. We welcome applications from all qualified candidates regardless of race, gender, age, religion, sexual orientation, or any other legally protected characteristics.
 
</div>

Human-AI Interface Research Assistant

THRAD

<div><h3 class="jobSectionHeader">The Role</h3>
We are looking for an Applied Scientist to own the models that decide which ad appears in which AI conversation, in real time, across millions of queries a day. Ad selection inside LLM chats is a genuinely new problem: no click history, no cookies, no page context. Just an evolving conversation and a few hundred milliseconds to make a decision that has to feel native to the user, relevant to the advertiser, and profitable for the publisher.
This is a research role with a production mandate. Your models go live, not into a paper. You will work directly with our CTO and the founding engineering team on the systems powering millions of ads a day across Fortune 500 campaigns.<h3 class="jobSectionHeader">
Core Tech Stack</h3><ul><li>
ML: PyTorch, embedding-based retrieval, modern transformer architectures</li><li>
Backend: Python (FastAPI), async serving, real-time inference</li><li>
Data: PostgreSQL for transactional, ClickHouse for analytics and event data</li><li>
Infra: AWS, Docker, CI/CD</li><li>
Plus: whatever the problem demands. We pick tools that ship.</li></ul><h3 class="jobSectionHeader">
Example Projects</h3><ul><li>
Design and train contextual ad relevance models for LLM conversations, from retrieval through ranking through creative selection.</li><li>
Build efficient algorithms for real-time bidding and auction mechanics, balancing publisher yield and advertiser ROAS.</li><li>
Productionize regression models to predict downstream conversion from early conversational signals.</li><li>
Apply privacy-preserving clustering methods to categorize conversational context and improve advertiser targeting without compromising user data.</li><li>
Run live experiments against real traffic on our publisher network. Iterate on CTR, ROAS, and conversation quality metrics.</li><li>
Own the evaluation framework for ad quality, relevance, and user experience across the marketplace.</li><li>
Read an ArXiv paper on Monday. Have a prototype running on Friday.</li></ul><h3 class="jobSectionHeader">
What You Will Do</h3><ul><li>
Own the research and shipping of the models powering ad selection across Thrad's network.</li><li>
Move research to production end to end: hypothesis, training, evaluation, deployment, monitoring.</li><li>
Collaborate directly with the CTO and co-founders to translate research direction into working systems, often within the same day.</li><li>
Partner with the Data and Product teams to design and analyze live experiments on real traffic.</li><li>
Contribute to system architecture decisions as we scale from millions to billions of daily ad impressions.</li><li>
Communicate findings clearly to both technical and non-technical audiences across the team.</li></ul><h3 class="jobSectionHeader">
Who You Are</h3>
Must-haves<ul><li>
2 to 5 years of applied ML experience, ideally in ads, search, recommendations, ranking, or NLP.</li><li>
An advanced degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or a related field &mdash; or equivalent experience shipping production ML.</li><li>
Strong fundamentals in mathematical and statistical modeling. You know why your model works, not just that it does.</li><li>
Fluent in PyTorch, modern transformer architectures, and embedding-based retrieval.</li><li>
Strong Python, comfort with distributed training and inference.</li><li>
You have shipped ML to production at scale. Not just notebooks.</li><li>
You enjoy identifying and owning hard, open-ended problems. You form testable hypotheses and run them to ground.</li><li>
Based in San Francisco or willing to relocate. This is an in-person role at our SF HQ.</li></ul>
Nice-to-haves<ul><li>
Experience with RLHF, preference modeling, or LLM fine-tuning.</li><li>
Background in auction theory, bidding systems, real-time pricing, or yield optimization.</li><li>
Prior work at an ad-tech, search, recommendations, or marketplace company.</li><li>
Published research at NeurIPS, ICML, ACL, KDD, RecSys, or equivalent.</li><li>
Familiarity with ClickHouse or other column-oriented OLAP databases for analytical workloads.</li><li>
A relentless interest in the AI and LLM ecosystem and how advertising will evolve inside conversational interfaces.</li></ul><h3 class="jobSectionHeader">
Why Thrad</h3><ul><li>
First mover: We are defining a new category. Paid ads in AI is an inevitable market and we are building the infrastructure for it.</li><li>
Real traction: Fortune 500 clients, millions of daily impressions, and publisher partners across the AI web, all pre-seed.</li><li>
Research with teeth: Your work ships. Your models run in production against real traffic with real revenue on the line.</li><li>
Direct impact: Small founding team. Your decisions shape the models, the product, and the company.</li><li>
Ownership: Meaningful equity in a company at the intersection of two massive markets: AI and ad tech.</li><li>
Craft: A team that cares about shipping quality, not just quantity.</li></ul><h3 class="jobSectionHeader">
How to Apply</h3>
Send your CV and a brief note on what excites you about building at the intersection of AI and advertising. If you have published work, a GitHub, or models you have shipped that you are proud of, include them. We read every application.</div>

Applied Scientist

Genentech

<div><div><div>THE POSITION</div>
We advance science so that we all have more time with the people we love.
The Department of Cell and Tissue Genomics (CTG) is focused on developing and applying state of the art genomics technologies (e.g. single cell omics, high-content imaging, perturbations, etc) to solve key challenges in disease biology, target discovery, and translational medicine. We are seeking a highly talented, creative, and motivated computational biologist to analyze cutting-edge high-dimensional profiling and screening data, with a particular focus on high-content imaging, to decipher complex cellular circuits. The candidate will collaborate closely with members of the department to extract biological insights from diverse high dimensional data sets and support the development of new technologies, leveraging existing computational workflows and developing novel ones.
The Opportunity:
As an integral member of our dynamic team, you will be:<ul><li>
Analyzing high-content imaging data from novel technologies including optical pooled screens, spatial transcriptomics, and high-content perturbation screens, with the goal of extracting mechanistic insights into gene function and cellular phenotypes.</li><li>
Developing methods to analyze and interpret new types of perturbation data.</li><li>
Applying statistics and machine learning to investigate data and extract biological insights.</li><li>
Collaborating across diverse, cross-functional teams including experimentalists in CTG and the therapeutic areas and colleagues in the Computational Sciences Center of Excellence and the AI Biology &amp; Translation departments</li></ul>
Who You Are:<ul><li>
PhD in Computational Biology, Bioinformatics, Computer Science, or a related quantitative field. Alternatively, a PhD in molecular biology, immunology, bioengineering, etc. combined with a very strong record of data analysis, supported by publication in this area. Postdoctoral training is a plus.</li><li>
Strong publication record of biological discovery and/or methods development.</li><li>
Deep expertise in image analysis, including image processing, feature extraction, and morphological profiling. Familiarity with modern deep learning approaches (e.g., embeddings, foundation models) is a plus.</li><li>
Comfortable with the statistical principles behind current best practices in high-throughput data analysis.</li><li>
Fluent in Python and/or R.</li><li>
Excellent communication and presentation skills.</li><li>
Able to work successfully in cross-functional teams to collaboratively solve complex problems.</li><li>
Passionate about applying your analytical skills to understand health and disease.</li></ul>
Preferred Experience:<ul><li>
Experience with in situ data (FISH or ISS barcode calling).</li><li>
Familiarity with image analysis frameworks or libraries (e.g., CellProfiler).</li><li>
Experience with genomic data including single cell RNA-seq and perturbation screens is a plus.</li><li>
Experience with applying machine learning to high throughput datasets is a plus.</li></ul>
Relocation benefits are available for this posting.
The expected salary range for this position based on the primary location of California for Senior Scientist is $124,300- $230,900 and Principal Scientist is $143,200-$265,900. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.
Benefits
Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.
If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.</div>
<div><div>JOB FACTS
</div><div><div><ul><div>Job Sub Category
Research Informatics
</div><div>Schedule
Full time
</div><div>Job Type
Regular
</div><div>Posted Date
Apr 10th 2026
</div><div>Job ID
202604-108731</div></ul></div></div></div></div>

Computational Scientist 3 - Cell & Tissue Genomics

<div>
 
 Overview
 
 
 
 Handshake is recruiting exceptional graduates with a master&rsquo;s in Pharmacy (MPharm, PharmD, or equivalent) to join our AI research community. This program brings subject-matter experts together to enhance the capabilities of Large Language Models (LLMs) within specialized domains and subdomains. The Handshake AI Fellowship program runs year-round, though project availability will vary by domain.
 
 
 
 About Handshake AI
 
 
 
 About Handshake AI
 
 
 Details
 
 
 <ul>
 <li>
 The position is remote and asynchronous - work independently from wherever you are.
 </li>
 <li>
 Flexible hours and the ability to work remotely, with no minimum commitment to hours.
 </li>
 <li>
 Project work includes and is not limited to developing domain-specific prompts and evaluating LLM responses.
 </li>
 <li>
 Dedicate time researching topics that are interesting to you, with the assistance of AI.
 </li>
 <li>
 Learn new skills while contributing to the changing world of AI across various disciplines.
 </li>
 <li>
 Placement into a project will be dependent on project availability.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Must have a master's from a US institution
 </li>
 <li>
 Able to participate in primarily asynchronous work in partnership with leading AI labs.
 </li>
 <li>
 Believe your expertise can outmatch current AI systems in understanding and explaining key concepts in your field.
 
 
 </li>
 </ul>
 Selection for each project is limited to a small cohort chosen for their disciplinary and research expertise. We are seeking experts in new research areas to test the limits of the world&rsquo;s top LLMs&rsquo; scientific and language understanding by completing tasks that impact the next frontier AI model.
 
 
 Work authorization information
 
 
 F-1 students who are eligible for CPT or OPT may be eligible for projects on Handshake AI. Work with your Designated School Official to determine your eligibility. If your school requires a CPT course, Handshake AI may not meet your school&rsquo;s requirements. STEM OPT is not supported. for more information on what types of work authorizations are supported on Handshake AI.
</div>

Pharmacy Expert

Anthropic

<div><div><h2 class="jobSectionHeader">About Anthropic</h2>

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.</div><div><h2 class="jobSectionHeader">
About the role</h2>

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.

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.
<h2 class="jobSectionHeader">
Responsibilities:</h2>
<ul>
<li>Deliver high-impact analyses and deep dives that surface key insights about Anthropic's financial performance directly to finance and executive leadership
</li>
<li>Build and maintain canonical datasets, dashboards, and scaled reporting solutions that provide real-time financial visibility across the company
</li>
<li>Partner with Finance &amp; Strategy teams (Product, Compute, GTM, and Corporate) to answer their most important questions and streamline recurring analytical workflows
</li>
<li>Establish analytics engineering and BI best practices for F&amp;S, including data management, governance, and reporting standards
</li>
<li>Partner with Data Infrastructure, Analytics Engineering, and Financial Systems teams to develop scalable data pipelines supporting finance and accounting analytics
</li>
<li>Champion data-informed decision making across the organization
</li>
</ul><h2 class="jobSectionHeader">You may be a good fit if you:</h2>
<ul>
<li>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
</li>
<li>Are highly proficient in SQL and Python for analysis, data manipulation, ETL/ELT, and automation
</li>
<li>Have a track record of producing analyses that have meaningfully influenced business or leadership decisions
</li>
<li>Have extensive experience with data visualization and using Claude / AI tools for data analysis and BI
</li>
<li>Have experience with cloud platforms (AWS, GCP) and modern data stack tools (dbt, Airflow, etc.)
</li>
<li>Have hands-on experience working with financial systems and building downstream data models from these systems
</li>
<li>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
</li>
<li>Are detail-oriented with a deep commitment to data accuracy
</li>
<li>Thrive in fast-paced environments, can manage multiple priorities while maintaining high-quality deliverables
</li>
<li>Operate with an ownership mindset, taking projects end-to-end from ambiguous question to trusted answer and seeing them through to impact
</li>
</ul><h2 class="jobSectionHeader">Strong candidates may have:</h2>
<ul>
<li>Championed AI driven analytics and financial analysis within their organizations
</li>
<li>Prior experience in high-growth technology companies or startups
</li>
<li>Strong financial acumen with deep understanding of finance principles
</li>
<li>Knowledge of statistical analysis and advanced analytics techniques
</li>
<li>Familiarity with data governance best practices and experience implementing data quality frameworks
</li>
</ul></div><div><div><div><div>The annual compensation range for this role is listed below.

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.</div></div><div>
Annual Salary:</div><div>
$270,000 - $320,000 USD</div></div></div><div><h2 class="jobSectionHeader">
Logistics</h2>

Minimum education: Bachelor&rsquo;s degree or an equivalent combination of education, training, and/or experience

Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Location-based hybrid policy: 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.

Visa sponsorship: 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.

We encourage you to apply even if you do not believe you meet every single qualification. 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. 
 
Your safety matters to us. 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.
<h2 class="jobSectionHeader">
How we're different</h2>

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.

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.
<h2 class="jobSectionHeader">
Come work with us!</h2>

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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process</div></div>

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