Come join the company that is reinventing cloud security and empowering businesses to thrive in the cloud. As the fastest-growing startup ever, Wiz is on a mission to help organizations secure cloud environments that will accelerate their businesses. Trusted by security teams all over the world, we have a proven track record of success and a culture that values world-class talent.
Our Wizards from over 13 countries work together to protect the infrastructure of our hundreds of customers, including over 45% of the Fortune 100, who trust us to scan and secure over 230 billion files daily. We’re the leading player in a massive and growing market, but it’s still early enough for you to make a significant impact. At Wiz, you’ll have the freedom to think creatively, dream big, and use your full range of skills to contribute to our record growth. Come join our team and help us create secure cloud environments that allow the best companies to move faster.
SUMMARY
We’re looking for a Data Classification Researcher to join the AI Research Team and help spread the power of Wiz. In this role, you will push the boundaries of data security and insight extraction in cloud environments. You'll be at the forefront of developing sophisticated methods to classify and secure sensitive data, addressing challenges like unstructured data and document files. Operate at a large scale and collaborate with some of the largest customers in the world.
WHAT YOU’LL DO
- Develop advanced classification tools and methods to accurately identify sensitive data stored in cloud services like AWS, Azure, and GCP.
- Research and analyze sensitive data, including the identification of Personally Identifiable Information (PII) and secrets such as passwords and API tokens, across both structured (JSON/CSV, etc.) and unstructured formats (code, text).
- Identify and assess data security risks and use cases within cloud environments.
- Collaborate with data scientists, engineering, and product teams to drive data-driven product decisions for large-scale projects, working closely with our biggest customers.
- Leverage Large Language Models (LLMs) and advanced AI technologies to enhance data processing and analytical workflows, improving efficiency and accuracy.
WHAT YOU’LL BRING
- Bachelor's or Master's degree in a field related to data science, such as computer science, statistics, or mathematics, or equivalent experience.
- 3+ years of hands-on experience in research and analysis of large datasets.
- Proficiency in Python, along with experience in using data science libraries and frameworks such as Pandas, NumPy, and Scikit-learn.
- Strong understanding of database management systems with expertise in SQL and experience using data warehousing solutions such as Snowflake or BigQuery.
- Excellent analytical, problem-solving, and critical thinking skills.
- Ability to address challenges associated with unstructured data and document files.
- Highly motivated, self-driven, and capable of working both independently and collaboratively within a team.
- Excellent English communication skills, both spoken and written.
ADVANTAGE
- Experience with Large Language Models (LLMs) and prompt engineering.
- Expertise in creating AI knowledge bases and implementing Retrieval-Augmented Generation (RAG) techniques.
- Familiarity with developing agentic workflows to automate data processing and insights.
Wiz is on a mission to build a special company. To achieve our goal, we are focused on hiring Wizards with different backgrounds, perspectives, and experiences.
Wiz is an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law.
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