Data Scientist - Managed Rules

Key Skills

Unix Operating system, Python Programming, SQL, Scala Programming, Machine learning techniques, Google BigQuery, Deep Learning, Tableau, Apache Hive, Google Analytics, Statistical modeling

Job Description

At Cloudflare, we have our eyes set on an ambitious goal: to help build a better Internet. Today the company runs one of the world’s largest networks that powers approximately 25 million 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. 

We realize people do not fit into neat boxes. We are looking for curious and empathetic individuals who are committed to developing themselves and learning new skills, and we are ready to help you do that. We cannot complete our mission without building a diverse and inclusive team. We hire the best people based on an evaluation of their potential and support them throughout their time at Cloudflare. Come join us! 

About The Team

The Managed Rules Team is working on building the best in class Web Application Firewall (WAF). We do this by maintaining the rules that make up the WAF (based on wirefilter) and proactively looking for the next vulnerabilities across levels 3-7 of the OSI Model. We can do this by using our massive amounts of data, and work in tandem with vendors to add WAF-based protections before vulnerabilities are disclosed. We accomplish these goals by building the next generation of tools to quickly identify and address vulnerabilities. In response our tooling enables us to iterate quickly on rules, as well as deploying with confidence to our millions of customers. We are a polyglot team that utilizes Rust, Go, and Python to build our services and tools.

Responsibilities

This is a senior role. Part of helping spin up this team is to define the responsibilities. This includes crafting the KPIs, desired outputs for data science in the context of the WAF team’s goals, as well as milestones and implementation details. We anticipate a diverse set of additional responsibilities that includes the following:

• Partner with product managers, data engineers, and other key stakeholders in understanding the need for data insights and predictive analytics in the area of security and fraud detection in a globally distributed environment.
• Understand data landscape i.e tooling, tech stack, source systems etc. and work closely with the Managed Rules engineers to improve the data collection and quality.
• Understand business/product strategy and high-level roadmap and align analysis efforts to enable them with data insights and help achieve their strategic goals.
• Ability to define and spot macro and micro levels trends with statistical significance on a regular basis and understand key drivers driving those trends.
• Define, implement, and train statistical, machine learning, and deep learning models.
• Use software engineering best practices to publish model scores/insights/learnings at scale within the company and externally as part of our Security thought leadership.

Requirements

Understand data landscape, i.e tooling, tech stack, source systems and work closely with the data engineers and machine learning engineers to improve the data collection and quality.

• M.S or Ph.D in Computer Science, Statistics, Mathematics, or other quantitative field.
• 5+ years of data scientist experience with proven industry experience in a large scale environment (PBs scale, globally distributed teams).
• Strong experience in scientific computing using Python, Scala, or equivalent.
• Experience with Spark, SQL, Tableau, Google Analytics, Hive and BigQuery (or any other Big data/Cloud equivalent).
• Experience in defining, implementing, and training statistical, machine learning, and deep learning models.
• Experience in using software engineering best practices to publish modelscores/insights/learnings atscale within the company.
• Proven ability to define and spot macro and micro levels trends with statistical significance on a regular basis and understand key drivers driving those trends.
• Experience working with and processing structured, unstructured, and semi-structured data.
• Proven track record of applying data insights and machine learning in order to address business needs and drive revenue.
• Strong communication and presentation skills catered to different audiences within the company.
• Capable of working closely with business, engineering, and product teams to ensure data initiatives are aligned with business needs.
• Strong data analytical skills, taking initiative in deriving data insights and thread intelligence, and proposing models and solutions that can lead to quick and effective proof-of-concept (POC).
• Strong audience-focused presentation and storytelling skills focused on key takeaways in a crisp and concise manner.

Nice To Haves

Experience with cyber security, fraud detection, Internet & network protocols

• Experience in productizing machine learning models
• Familiarity writing and optimizing advanced SQL queries in Clickhouse
• Good Linux/UNIX systems knowledge