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REBAR

<div>About Rebar 
Rebar is building the operating system for commercial HVAC, Electrical, and Plumbing suppliers. As our AI-powered quoting engine scales across top suppliers in North America, measurement and evaluation become critical infrastructure. 
 
As a Data Analytics Engineer, you will build the systems that help us understand how our AI performs in the real world &mdash; where it succeeds, where it fails, and how it impacts downstream business outcomes. You will define core product metrics, implement monitoring frameworks, and ship internal and customer-facing data products that turn raw model outputs into trusted intelligence. 
 
This role sits at the intersection of AI evaluation, product analytics, and data-driven product development. You will be responsible both for developing new derivative data products that create value for our customers, as well as understanding how our AI systems succeed and fail in the real world, tracking those dynamics over time, and helping build derivative data products that create value for both internal teams and customers. This role is ideal for someone who enjoys building measurement systems and analytics infrastructure as much as answering business questions. 
 
Required Qualifications<ul><li>
Bachelor&rsquo;s or Master's degree in Computer Science, Data Science, or other relevant field.</li><li>
Strong Python skills, SQL proficiency, and experience with Data Warehousing</li><li>
Experience working with large, real-world datasets and ambiguous problem definitions.</li><li>
Experience writing modular, testable analytics code and working in version-controlled environments.</li><li>
Ability to design meaningful metrics and evaluation frameworks for complex systems from scratch.</li><li>
Experience building data visualizations and dashboards.</li><li>
1&ndash;3 years of experience in analytics engineering, data science, or product analytics roles working with production data systems.</li><li>
Comfortable communicating quantitative insights to both technical and non-technical stakeholders.</li></ul>
Responsibilities<ul><li>
Help design and build data-driven product features on top of Rebar&rsquo;s historical datasets.</li><li>
Define, implement, and productionize metrics to measure AI system performance over time, including automated tracking and monitoring of regressions and drift.</li><li>
Analyze model failure modes across documents, projects, customers, and time &mdash; and communicate findings clearly to ML and product teams.</li><li>
Build durable data models, dashboards, internal tools, and lightweight product features that expose metrics, trends, and confidence signals to both internal teams and customers.</li></ul>
Nice to Have<ul><li>
Experience evaluating or monitoring ML systems in production.</li><li>
Familiarity with computer vision, NLP, or AI-driven products.</li><li>
Experience working at a startup or in a fast-moving product environment.</li></ul>
Compensation and Benefits<ul><li>
Salary: $130-185K, dependent on experience</li><li>
Equity: Meaningful equity package, commensurate with experience</li><li>
Benefits: Comprehensive medical, dental, and vision coverage</li></ul>
This is a salaried, onsite role based in NYC (Flatiron).</div>

Data Analytics Engineer

Resonance

<div>
 
 About Us
 
 
 
 Resonance is transforming the fashion industry by building a more sustainable and valuable ecosystem for designers, brands, manufacturers, consumers, and the planet. Our AI-powered operating system, ONE, empowers brands to design, sell, and make products efficiently and sustainably. Resonance ONE drives end-to-end garment creation with minimal environmental impact, eliminating overproduction and unnecessary inventory.
 
 
 With headquarters in New York City and Santiago, Dominican Republic, Resonance partners with leading brands&mdash;including THE KIT and Rebecca Minkoff&mdash;to significantly reduce resource use: 97% less dye, 70% less water, and 50% less material compared to traditional fashion brands.
 
 
 
 About The Role
 
 
 
 We&rsquo;re seeking a talented Data and Analytics Engineer to build, maintain, and scale our data infrastructure. You&rsquo;ll play a crucial role in shaping our analytical capabilities, enabling Resonance to leverage data-driven insights effectively across our complex, integrated technology stack.
 
 
 In this role, you&rsquo;ll develop and maintain robust ELT pipelines, transforming data from diverse sources&mdash;including telemetry data, Shopify, SendGrid, CreateOne, and other internal platforms&mdash;into structured, accessible datasets within Snowflake. Additionally, you&rsquo;ll craft sophisticated LookML models to power interactive analytics, dashboards, and explorers used daily by our business teams.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Design, build, and maintain scalable ELT pipelines that reliably transform raw data from sources such as Shopify, SendGrid, telemetry services, and proprietary applications (CreateOne) into our Snowflake data lake and data warehouses.
 </li>
 <li>
 Create efficient, maintainable data models within Snowflake that serve as the foundation for analytics, reporting, and data-driven decision-making.
 </li>
 <li>
 Develop and refine LookML models, enabling intuitive exploration, dashboards, and actionable analytics for non-technical business users.
 </li>
 <li>
 Collaborate closely with product teams, engineers, and business stakeholders to identify data needs, gather requirements, and deliver high-impactdata solutions.
 </li>
 <li>
 Continuously improve data quality, governance, and accessibility, implementing best practices for data management and compliance.
 </li>
 <li>
 Proactively monitor and optimize ELT performance, reliability, and cost-effectiveness.
 </li>
 <li>
 Stay updated on the latest data engineering technologies, approaches, and analytics tools to ensure Resonance maintains industry-leading capabilities.
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 
 Minimum Qualifications
 
 
 
 <ul>
 <li>
 4+ years of relevant experience in data engineering, analytics engineering, or a related field.
 </li>
 <li>
 Strong proficiency in building robust ELT/ETL data pipelines using modern tools and practices.
 </li>
 <li>
 Hands-on experience with Snowflake or similar cloud data warehousing platforms.
 </li>
 <li>
 Proficiency with SQL and database modeling techniques for analytics.
 </li>
 <li>
 Experience building analytics layers and semantic models (LookML strongly preferred; experience with similar BI tools like dbt or Tableau considered).
 </li>
 <li>
 Familiarity integrating data from external sources such as Shopify, SendGrid, or other SaaS platforms.
 </li>
 <li>
 Strong analytical mindset, problem-solving capabilities, and attention to detail.
 </li>
 <li>
 Excellent collaboration and communication skills in remote, cross- functional environments.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Previous startup or rapid-growth environment experience.
 </li>
 <li>
 Advanced knowledge of Snowflake performance optimization and cost management.
 </li>
 <li>
 Experience with Looker, LookML, and creating intuitive, interactive analytics products.
 </li>
 <li>
 Familiarity with Python scripting for data pipelines and automation.
 </li>
 <li>
 Interest or experience in sustainability, e-commerce, fashion-tech, or manufacturing domains.
 
 
 </li>
 </ul>
 
 Benefits
 
 
 
 We offer comprehensive benefits (medical, dental, and vision), competitive salary, equity participation, and remote work flexibility.
 
 
 Resonance Companies is an equal opportunity employer committed to diversity, inclusion, and innovation. All employment decisions are based solely on qualifications, merit, and business need.
</div>

Data and Analytics Engineer

sent

<div>About Sent
Sent is an infrastructure for sending A2P messages across SMS, WhatsApp, and RCS through a single unified API. Our intelligent routing model automates channel selection based on deliverability and cost, ensuring lower cost and global reach without any channel-specific integrations.
We recently closed a $5.1M Seed round backed by Companyon Ventures, Bessemer Venture Partners, UIF, and CEAS Investments. We're hiring to build the best infrastructure to replace multi-channel messaging stacks.
We're hiring a Data &amp; Analytics Engineer to build Sent's data infrastructure from the ground up. You'll design the pipelines, models, and dashboards that make messaging performance, revenue, and operational health legible across the company &mdash; and eventually, directly to our customers.
About the Role
Sent processes millions of messages across SMS, WhatsApp, and RCS. The data those messages generate tells a story about delivery performance, carrier behavior, customer growth, and product quality. Right now, much of that story is untold. You'll be the person who builds the systems to surface it.
You'll work directly with leadership, engineering, and go-to-market to define the metrics that matter, instrument the platform to capture them, and build the reporting that drives decisions. This is a foundational hire - you'll have significant ownership and influence over how the company uses data.
In this role, you will&hellip;<ul><li>
Design and build data pipelines that turn raw messaging events into structured, queryable data.</li><li>
Build internal dashboards and reporting tools that drive decisions across sales, ops, product, and engineering.</li><li>
Define and maintain core KPIs - delivery rates, latency, carrier performance, customer health, revenue metrics.</li><li>
Partner with engineering to improve logging, instrumentation, and data capture across the platform.</li><li>
Lay the groundwork for customer-facing analytics (delivery dashboards, message performance insights).</li><li>
Support financial and operational reporting as the company scales.</li></ul>
You'll be a great fit if you&hellip;<ul><li>
Have 3+ years in analytics engineering, data engineering, or a similar role.</li><li>
Are strong in SQL and experienced with modern data stack tools (dbt, Snowflake/BigQuery, Airflow, Fivetran, or similar).</li><li>
Have built dashboards in tools like Metabase, Looker, or Grafana.</li><li>
Are comfortable working with event-driven data and high-volume systems.</li><li>
Can write Python or a similar scripting language for data manipulation.</li><li>
Have a bias toward building things that are clean, well-documented, and maintainable.</li></ul>
Nice to have<ul><li>
Experience at an API-first company.</li><li>
Familiarity with PostHog or similar product analytics tools.</li><li>
Exposure to usage-based pricing models and how to measure unit economics.</li><li>
Experience building customer-facing data products or analytics features.</li></ul>
Our Commitment to You<ul><li>
Meaningful equity with high growth potential</li><li>
Top-tier medical, dental, vision fully covered</li><li>
401(k) with 100% match up to 4%</li><li>
Unlimited PTO</li><li>
Beautiful NYC workspace with daily meals and unlimited snacks</li><li>
New MacBook Pro + Apple Studio Display</li><li>
Fully comped Wellhub Gold or Equinox membership</li></ul>
Sent, Inc. is an Equal Opportunity Employer committed to building a diverse and inclusive team. We encourage applications from candidates of all backgrounds and experiences.
Compensation Range: $130K - $160K</div>

Data Engineer, Product Analytics

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
Are you passionate about Big Data, Distributed systems, and large scale datasets can be integrated with new state-of-the-art AI agent-friendly data interfaces? Be part of a team of world-class engineers and industry leading experts operating one of the largest big data platforms for advertising at Amazon scale. 
 
Key job responsibilities 
Join our team and take ownership of significant initiatives that solve some of the toughest technical challenges in big data: 
<ul><li>Design and build highly scalable, fault-tolerant data pipelines processing petabytes of advertising data</li><li>Architect new data paradigms that enable real-time analytics and machine learning applications</li><li>Collaborate with data scientists, product managers, and partner teams across Amazon Ads to deliver data solutions that drive business impact</li><li>Mentor junior engineers through code reviews, design discussions, and pair programming</li><li>Contribute to technical strategy and architectural decisions for our data platform</li><li>Build monitoring, alerting, and data quality frameworks to ensure reliability at scale</li></ul> 
Our systems are built for stability and reliability, which means our on-call shifts are manageable and focused on continuous improvement rather than firefighting. 
 
About the team 
We're a collaborative team of engineers who are passionate about solving complex data challenges while maintaining a healthy work-life balance. Our engineers regularly work with latest technologies&mdash;recent projects include migrating our data lake to Apache Iceberg, implementing real-time streaming pipelines with Spark, and building unified and flexible reporting solutions. We invest heavily in your growth through mentorship programs, technical design reviews, and opportunities to present at internal tech talks. We believe in sustainable engineering practices with reasonable on-call rotations (typically one week per quarter) and flexible work arrangements.</div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>3+ years of non-internship professional software development experience</li><li>2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience</li><li>1+ years of big data technologies such as AWS, Hadoop, Spark, Pig, Hive, Lucene/SOLR or Storm/Samza experience</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>4+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience</li><li>4+ years of contributing to new and current systems architecture and design (architecture, design patterns, reliability and scaling) experience</li><li>Experience building and operating data pipelines using Apache Spark and Scala on Amazon EMR, spanning extraction, ingestion, batch and streaming processing. Data lake design with Apache Iceberg a plus.</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, NY, New York - 158,100.00 - 213,800.00 USD annually</div>

Software Development Engineer - Big Data, Brand Metrics and Benchmarks

Anthropic

<div>
 
 
 About Anthropic
 
 
 
 
 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.
 
 
 
 Job Description
 
 
 
 
 About the role
 
 
 
 As part of our growing Data Science and Analytics team, you will play an instrumental role in our company&rsquo;s mission of building safe and beneficial artificial intelligence by driving data-informed decision making across our organization. You&rsquo;ve worked in cultures of excellence in the past, and are eager to apply that experience to help shape the cultural norms and best practices of a growing data science team as Anthropic continues to scale. In this unique company, technology, and moment in history, your work will be critical to informing our strategy as we deploy safe, frontier AI at scale to the world.
 
 
 
 
 Core Responsibilities
 
 
 
 
 <ul>
 <li>
 Define key metrics, build measurement frameworks, and maintain core reporting to evaluate success
 </li>
 <li>
 Deep dive into product and user data to derive actionable insights and size opportunities to improve products, strategy and operations, influencing roadmaps through insights and recommendations
 </li>
 <li>
 Develop hypotheses, apply rigorous causal inference methods &ndash; controlled experiments, synthetic controls &ndash; and analyze the results in order make actionable recommendations
 </li>
 <li>
 Investigate anomalies, conduct root cause analyses, and provide data-driven insights to guide priorities and inform decisions
 </li>
 <li>
 Build statistical models, optimization frameworks, and simulations to automate decision-making and operational processes
 </li>
 <li>
 Present complex analyses and recommendations to both technical and non-technical stakeholders
 </li>
 <li>
 Establish foundational data practices and help scale our analytics infrastructure to support rapid iteration and decision-making as our products grow
 
 
 </li>
 </ul>
 
 
 You May Be a Good Fit If You Have:
 
 
 
 
 <ul>
 <li>
 5+ years of experience in data science or analytics roles
 </li>
 <li>
 Deep expertise with Python, SQL, and data visualization tools
 </li>
 <li>
 Expertise with experimental design, causal inference, statistical modeling, and A/B testing frameworks, particularly in high-scale technical environments
 </li>
 <li>
 Highly effective written communication and presentation skills
 </li>
 <li>
 A track record of translating complex data into clear, actionable insights for both technical and business stakeholders
 </li>
 <li>
 A bias for action and ability to thrive in ambiguous, fast-moving environments where you must create clarity and drive forward progress
 </li>
 <li>
 A passion for the company&rsquo;s mission of building helpful, honest, and harmless AI
 </li>
 <li>
 Some experience with AI/ML products, large language models, or developer tools in the AI/ML ecosystem
 
 
 </li>
 </ul>
 We&rsquo;re hiring across multiple pillars
 
 
 Applying for this role will allow you to be considered for all pillars currently hiring. You will be asked to select a preference when submitting an application.
 
 
 
 Platform Product Data Scientist
 
 
 
 You will partner closely with product, engineering, and go-to-market teams to understand how developers and enterprise customers build on and adopt the Claude Developer Platform&mdash;spanning our core API, agent orchestration, tool and MCP integrations, and knowledge management capabilities. You'll identify growth opportunities, surface insights about how AI agents are being built and deployed at scale, and drive data-informed decisions that shape our platform roadmap.
 
 
 
 Strong Candidates May Have:
 
 
 
 <ul>
 <li>
 3+ years of experience working closely with Product or Engineering teams on API or developer-facing products, with demonstrated impact on product roadmap and strategy
 </li>
 <li>
 Experience supporting B2B sales teams with data insights
 </li>
 <li>
 Strong instincts for what drives product adoption, engagement, and retention
 
 
 </li>
 </ul>
 
 Consumer Data Scientist
 
 
 
 You will be embedded with our Consumer product team. This team is responsible for building all consumer-facing Claude experiences&mdash;including web, mobile, desktop, and browser extensions. In this role, you'll shape how millions of users interact with Claude daily, driving product insights to product recommendations for interfaces that are intuitive, responsive, and push the boundaries of what AI-powered applications can be.
 
 
 
 Strong Candidates May Have:
 
 
 
 <ul>
 <li>
 Experience working closely with Product and Engineering teams on consumer products across multiple platforms (web, iOS, Android, desktop, browser extensions)
 </li>
 <li>
 Demonstrated impact on product roadmap and strategy from data deep dives in consumer growth, engagement and retention
 </li>
 <li>
 Expert in experimentation, holding a high statistical bar for measuring the impact of core product changes
 
 
 </li>
 </ul>
 
 Research Product Data Scientist
 
 
 
 You will work closely with product, engineering, and research leaders to bring data-driven rigor to every phase of model development and launch. Sitting at the true bleeding edge of putting frontier AI research into the public domain, you will leverage data from both external customers and internal testing to define and measure key company success metrics, and analyze user and model behavior to identify new opportunities to push the frontier.
 
 
 
 Strong Candidates May Have:
 
 
 
 <ul>
 <li>
 3+ years of experience deeply embedding in Product or Research teams, preferably working with LLM or AI products
 </li>
 <li>
 Comfort working with unstructured data
 
 
 </li>
 </ul>
 
 Enterprise &amp; Verticals Product Data Scientist
 
 
 
 You will be embedded with our Enterprise &amp; Verticals product team - this team is responsible for transforming the way businesses work, enabling enterprise users to know more, create more, and see more with Claude. You'll partner closely with product, engineering, design, sales, and customer success to understand enterprise customers and deliver data-driven insights to improve how Claude serves knowledge workers.
 
 
 
 Strong Candidates May Have:
 
 
 
 <ul>
 <li>
 Experience evaluating new verticals and driving data insights to help the team find PMF for 0-&gt;1 bets
 </li>
 <li>
 Deep understanding over knowledge workers and experience partnering with product teams to build for the Enterprise
 
 
 </li>
 </ul>
 
 Claude Code Enterprise Product Data Scientist
 
 
 
 You will be embedded with our Claude Code product team to drive data-informed decision making as we scale this revolutionary developer tool to meet the needs of Enterprise businesses. Working at the intersection of AI capabilities research and product development, you'll help us understand how developers interact with AI coding assistants, measure the impact of our tool on developer productivity, and identify opportunities to enhance the developer experience.
 
 
 
 Strong Candidates May Have:
 
 
 
 <ul>
 <li>
 Deep familiarity with software development workflows, developer tools, and engineering productivity metrics&mdash;ideally from working at developer-focused companies or on products targeting software engineers
 </li>
 <li>
 Experience analyzing human-AI interaction patterns, particularly in code generation or developer tooling contexts
 </li>
 <li>
 Experience supporting product teams building for the Enterprise
 
 
 </li>
 </ul>
 
 Enterprise Marketing Data Scientist
 
 
 
 You will work closely with marketing, product, and commercial teams to define and measure key marketing success metrics, analyze customer acquisition and retention, and build a culture of developing and testing hypotheses through experimentation as we introduce Claude to Enterprise businesses.
 
 
 
 Strong Candidates May Have:
 
 
 
 <ul>
 <li>
 3+ years of experience deeply embedding in Marketing teams, turning marketing data into concise and insightful analysis that drives business outcomes
 </li>
 <li>
 Familiarity with both B2C and B2B/Enterprise marketing analytics, and a holistic view of how different marketing programs support one another
 </li>
 <li>
 Experience working at multi-segment, multi-product B2B companies serving Enterprise customers
 
 
 </li>
 </ul>
 
 Claude Code Marketing Data Scientist
 
 
 
 You will work closely with marketing, product, and commercial teams to define and measure key marketing success metrics, analyze customer acquisition and retention, and build a culture of developing and testing hypotheses through experimentation as we bring Claude Code to the world.
 
 
 
 Strong Candidates May Have:
 
 
 
 <ul>
 <li>
 3+ years of experience deeply embedding in Marketing teams, turning marketing data into concise and insightful analysis that drives business outcomes
 </li>
 <li>
 Familiarity with both B2C and B2B/Enterprise marketing analytics, and a holistic view of how different marketing programs support one another
 </li>
 <li>
 Experience building, selling or marketing developer tools
 
 
 </li>
 </ul>
 
 GTM Data Scientist
 
 
 
 This role sits at the intersection of fast-moving sales operations and rigorous statistical analysis. You will work across multiple segments and products, partnering with analytics engineers, fellow data scientists, and go-to-market leadership to turn messy, high-stakes commercial data into actionable strategy. You will play a crucial role in driving data-informed decisions across the commercial customer lifecycle&mdash;from new logo acquisition through activation, expansion, and retention&mdash;for a rapidly scaling consumption-based AI platform.
 
 
 
 Strong Candidates May Have:
 
 
 
 <ul>
 <li>
 A strong track record in multi-segment, multi-product B2B sales or commercial analytics, especially with consumption-based revenue models
 
 
 </li>
 </ul>
 
 Infrastructure Data Scientist
 
 
 
 You'll be at the intersection of data science and infrastructure, using rigorous analysis to understand how platform performance impacts user behavior and identifying high-impact opportunities to improve our systems' reliability and responsiveness. You'll quantify user sensitivity to latency, reliability, errors, and refusal rates, then translate these insights into actionable recommendations that drive meaningful improvements to our platform infrastructure.
 
 
 
 Strong Candidates May Have:
 
 
 
 <ul>
 <li>
 Experience with distributed systems and performance engineering, ideally in ML infrastructure contexts (model serving, inference latency, large-scale system metrics)
 </li>
 <li>
 Familiarity with SRE practices, error budgets, SLOs/SLIs, observability tools, APM systems, and infrastructure monitoring platforms (e.g., Prometheus, Grafana, DataDog)
 
 
 </li>
 </ul>
 
 Developer Productivity Data Scientist
 
 
 
 This role sits at the intersection of data science, developer experience, and AI tooling &mdash; and offers the rare opportunity to study frontier AI usage from the inside, with the builders themselves as your users. You'll define how Anthropic understands and improves developer productivity &mdash; both through classic software engineering effectiveness measures and through the emerging challenge of understanding AI-augmented development workflows. You'll own the quantitative foundation for how Anthropic's engineers build: what slows them down, what accelerates them, where tooling investments pay off, and how AI-assisted development is changing the shape of engineering work. Your analyses will directly inform infrastructure priorities, tooling roadmaps, and how we think about scaling engineering output as Anthropic grows.
 
 
 
 Strong Candidates May Have:
 
 
 
 <ul>
 <li>
 Direct experience working with developer productivity, infrastructure, performance, or platform teams in hypergrowth environments
 </li>
 <li>
 Deep understanding of distributed systems, cloud infrastructure, and performance engineering, with experience analyzing large-scale system metrics
 
 
 </li>
 </ul>
 The annual compensation range for this role is listed below.
 
 
 For sales roles, the range provided is the role&rsquo;s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
 
 
 
 Annual Salary:
 
 
 
 $275,000&mdash;$370,000 USD
 
 
 
 Logistics
 
 
 
 
 Education requirements:
 
 We require at least a Bachelor's degree in a related field or equivalent experience.
 
 
 
 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.
 
 
 
 
 How We're Different
 
 
 
 
 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.
 
 
 
 Come work with us!
 
 
 
 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>

Data Scientist

Hudson Manpower

<div>About the Role
We are seeking a highly skilled Senior Data Architect / Application Engineer to join our team. In this role, you will be responsible for designing, implementing, and maintaining data platforms and application infrastructure. You will play a key role in driving innovative data solutions while ensuring platform reliability, security, and performance.
Location: New York City, NY (Hybrid &ndash; 3 days onsite)
Interview Process: In-person interview required in NYC.
Work Authorization: Only W2 candidates will be considered. C2C is allowed only if the candidate is a US Citizen or Green Card holder with their own corporation.
Key Responsibilities<ul><li>
Lead architecture and technical design discussions using industry best practices and modern technologies.</li><li>
Support production operations and resolve complex issues within the Credit Risk application platform.</li><li>
Design and implement batch and ad-hoc data pipelines using Medallion Lakehouse architecture on modern cloud platforms, primarily Databricks.</li><li>
Build and maintain data ingestion pipelines from upstream systems into object storage (e.g., S3, ADLS) using formats like Parquet, including partitioning, z-ordering, and schema evolution.</li><li>
Integrate with external XVA / risk engines and develop orchestration logic for long-running computations.</li><li>
Model and optimize risk metrics such as EPE and PFE for efficient querying and analytics.</li><li>
Ensure platform reliability, security, observability, and auditability, including IAM roles, authentication mechanisms, and encryption.</li><li>
Contribute to API design for internal and external consumers, including versioning, documentation, error handling, and SLAs.</li></ul> 
Required Qualifications
General<ul><li>
12&ndash;15 years of experience as an application developer or data engineer.</li><li>
Strong communication and collaboration skills.</li><li>
Experience working in Agile environments.</li><li>
Ability to design and document technical architectures and system designs.</li><li>
Proactive and self-driven team player with strong analytical skills.</li></ul> 
Technical Skills (Mandatory)<ul><li>
Python (expert level) including PySpark / Spark for data engineering.</li><li>
Azure Databricks with experience implementing Medallion Lakehouse Architecture.</li><li>
Strong SQL expertise including joins, unions, stored procedures, and query optimization.</li><li>
REST API development using frameworks such as Django, Flask, or FastAPI.</li><li>
Experience with CI/CD pipelines using Git, Jenkins, and Azure DevOps.</li><li>
Experience building data ingestion and transformation pipelines.</li><li>
Cloud platform certification such as AWS Certified Cloud Practitioner or equivalent.</li></ul> 
Domain Requirement<ul><li>
Strong experience in Credit Risk and Counterparty Risk within the financial services or capital markets domain.</li></ul> 
Preferred Qualifications<ul><li>
Advanced degree in Finance, Computer Science, or related field.</li><li>
Experience with risk modeling and financial analytics.</li><li>
Knowledge of deployment, operational support, and monitoring tools.</li><li>
Exposure to technical architecture design and system documentation.</li></ul></div>

Senior Data Architect / Application Engineer

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Senior Data Architect / Application Engineer