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About This Role
About Us
At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world's largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine's Top Company Cultures list and ranked among the World's Most Innovative Companies by Fast Company.
At Cloudflare, we're not looking for people who wait for a polished roadmap; we're looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a "normalized" problem and the AI\-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you're the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you'll fit right in.
Available Locations\- New York
About the Role
Cloudflare's Engineering Team is home to some of the industry's top engineers, dedicated to building and scaling innovative software that handles a huge proportion of the Internet. Our Detection department sits at the heart of that mission: we identify automated, fraudulent, and malicious activity across the Internet and through our gateway. We develop advanced detection systems and machine learning models that operate at scale, collaborating with Product and Engineering teams across the company to protect our customers and stay ahead of the constantly evolving threat landscape.
Responsibilities
- Research, design, and evaluate detection models that identify automated, fraudulent, and malicious activity across Internet\-scale data.
- Dig into massive datasets to uncover the patterns and behaviors that distinguish adversaries from legitimate users.
- Define how detection success is measured, designing metrics and evaluation strategies for problems where ground truth is noisy, delayed, or contested.
- Stay current on emerging AI/ML research and evaluate how new techniques (e.g., LLMs, generative AI) can be applied to our products.
- Partner with ML Engineers, Data Engineers, and Product to take detection approaches from research to production and measure their real\-world impact.
Desirable Skills, Knowledge, and Experience
- Fraud and bots at scale. You have experience across fraud, abuse, and/or bot detection on large, high\-velocity traffic. You may focus on one, but you transfer instincts between them.
- Strong fundamentals, fluent in data. You have solid applied statistics, machine learning, and AI methodology fundamentals. You choose the right technique for the problem, and are fluent with large\-scale data.
- You have at least 5\-7 years of experience professionally working in Data Science, ML Engineering, or Software Engineering.
- You are very comfortable with Python \& SQL in production environments.
Bonus points
- At home in ground truth ambiguity. Building detections when ground truth is scarce is the heart of this job. You make real progress with weak, delayed, or absent labels and you're energized by adversaries that fight back.
- You don't burn signals. You understand (or are curious to learn) how to act on detections without tipping your hand, knowing that how you deploy and respond can erode your future visibility.
- Pragmatic about complexity. You know when a simple solution beats a complex one, and you don't chase small gains at disproportionate cost.
- Disciplined in code. You apply strong programming and engineering best practices in both research and production code.
- Impact\-driven and clear. You connect your work to business impact and communicate clearly across technical and non\-technical stakeholders.
### Compensation
Compensation may be adjusted depending on work location.
- For New York City based hires: Estimated annual salary of $185,000 \- $231,000\.
### Equity
This role is eligible to participate in Cloudflare's equity plan.
Benefits
Cloudflare offers a complete package of benefits and programs to support you and your family. Our benefits programs can help you pay health care expenses, support caregiving, build capital for the future and make life a little easier and fun! The below is a description of our benefits for employees in the United States, and benefits may vary for employees based outside the U.S.
Health \& Welfare Benefits
- Medical/Rx Insurance
- Dental Insurance
- Vision Insurance
- Flexible Spending Accounts
- Commuter Spending Accounts
- Fertility \& Family Forming Benefits
- On\-demand mental health support and Employee Assistance Program
- Global Travel Medical Insurance
Financial Benefits
- Short and Long Term Disability Insurance
- Life \& Accident Insurance
- 401(k) Retirement Savings Plan
- Employee Stock Participation Plan
Time Off
- Flexible paid time off covering vacation and sick leave
- Leave programs, including parental, pregnancy health, medical, and bereavement leave
What Makes Cloudflare Special?
We're not just a highly ambitious, large\-scale technology company. We're a highly ambitious, large\-scale technology company with a soul. Fundamental to our mission to help build a better Internet is protecting the free and open Internet.
Project Galileo: Since 2014, we've equipped more than 2,400 journalism and civil society organizations in 111 countries with powerful tools to defend themselves against attacks that would otherwise censor their work, technology already used by Cloudflare's enterprise customers\-at no cost.
Athenian Project: In 2017, we created the Athenian Project to ensure that state and local governments have the highest level of protection and reliability for free, so that their constituents have access to election information and voter registration. Since the project, we've provided services to more than 425 local government election websites in 33 states.
1\.1\.1\.1: We released 1\.1\.1\.1 to help fix the foundation of the Internet by building a faster, more secure and privacy\-centric public DNS resolver. This is available publicly for everyone to use \- it is the first consumer\-focused service Cloudflare has ever released. Here's the deal \- we don't store client IP addresses never, ever. We will continue to abide by our privacy commitment and ensure that no user data is sold to advertisers or used to target consumers.
Sound like something you'd like to be a part of? We'd love to hear from you!
Please note that applicants who progress to the offer stage of the interview process may be asked to attend an in\-person interview within one of the Cloudflare Offices or Cloudflare Hubs. More details about this will be available at that stage of the interview process.
This position may require access to information protected under U.S. export control laws, including the U.S. Export Administration Regulations. Please note that any offer of employment may be conditioned on your authorization to receive software or technology controlled under these U.S. export laws without sponsorship for an export license.
Cloudflare is proud to be an equal opportunity employer. We are committed to providing equal employment opportunity for all people and place great value in both diversity and inclusiveness. All qualified applicants will be considered for employment without regard to their, or any other person's, perceived or actual race, color, religion, sex, gender, gender identity, gender expression, sexual orientation, national origin, ancestry, citizenship, age, physical or mental disability, medical condition, family care status, or any other basis protected by law. We are an AA/Veterans/Disabled Employer.
Cloudflare provides reasonable accommodations to qualified individuals with disabilities. Please tell us if you require a reasonable accommodation to apply for a job. Examples of reasonable accommodations include, but are not limited to, changing the application process, providing documents in an alternate format, using a sign language interpreter, or using specialized equipment. If you require a reasonable accommodation to apply for a job, please contact us via e\-mail at [email protected] or via mail at 101 Townsend St. San Francisco, CA 94107\.
Salary Context
This $185K-$231K range is above the 75th percentile for Data Scientist roles in our dataset (median: $155K across 226 roles with salary data).
View full Data Scientist salary data →Role Details
About This Role
Data Scientists extract insights and build predictive models from data. In the AI era, many roles now include LLM-powered analytics, automated reporting, and integration with generative AI tools. The role has evolved from 'the person who runs SQL queries' to 'the person who builds AI-powered data products.'
Modern data science roles fall into two camps: analytics-focused (insights, dashboards, experimentation) and ML-focused (building predictive models, recommendation systems, NLP features). The best data scientists can operate in both modes. The AI shift means that even analytics-focused roles now involve building automated insight pipelines using LLMs, going well beyond one-off reports.
Across the 3,708 AI roles we're tracking, Data Scientist positions make up 8% of the market. At Cloudflare, this role fits into their broader AI and engineering organization.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
What the Work Looks Like
A typical week includes: analyzing experiment results for a product feature launch, building a predictive model for customer churn, creating an automated reporting pipeline using LLM-powered summarization, presenting insights to stakeholders, and cleaning data (always cleaning data). The ratio of analysis to engineering varies by company, but expect both.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
Skills Required
Python, SQL, and statistical modeling are the foundation. Increasingly, roles want experience with LLMs for data analysis, automated insight generation, and building AI-powered data products. Familiarity with cloud data platforms (Snowflake, BigQuery, Databricks) and ML frameworks (scikit-learn, PyTorch) covers most job requirements.
Experimentation design and causal inference are underrated skills that separate strong candidates. Companies care about whether their product changes cause improvements, and can distinguish causation from correlation. A/B testing methodology, Bayesian statistics, and the ability to communicate uncertainty to non-technical stakeholders are high-value skills.
Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
Compensation Benchmarks
Data Scientist roles pay a median of $192,890 based on 463 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($208K) sits 8% above the category median. Disclosed range: $185K to $231K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Cloudflare AI Hiring
Cloudflare has 3 open AI roles right now. They're hiring across AI/ML Engineer, Data Scientist. Positions span Austin, TX, US, New York, NY, US. Compensation range: $231K - $231K.
Location Context
AI roles in New York pay a median of $220,000 across 1,045 tracked positions.
Career Path
Common paths into Data Scientist roles include Data Analyst, Statistician, Quantitative Researcher.
From here, career progression typically leads toward Senior Data Scientist, ML Engineer, AI Product Manager.
Start with statistics and SQL. Build a real analysis project on public data that demonstrates insight generation alongside model building. The market values data scientists who can communicate findings clearly to business stakeholders. If you want to move toward ML engineering, invest in software engineering fundamentals and production deployment skills.
What to Expect in Interviews
Interviews combine statistics, coding, and business acumen. SQL is almost always tested, often with complex joins and window functions. Expect a case study round where you're given a business problem and asked to design an analysis plan. Coding rounds focus on pandas, statistical modeling, and visualization. The strongest differentiator is how well you communicate insights to non-technical stakeholders during presentation rounds.
When evaluating opportunities: Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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