Data Scientist at Lacework

Data Scientist
Location:  Seattle & Bay Area 
Lacework: Lacework is the data-driven security platform for the cloud. The Lacework Cloud Security Platform, powered by Polygraph, automates cloud security at scale so our customers can innovate with speed and safety. Polygraph is the only security solution that can collect, analyze and accurately correlate data across an organization’s AWS, Azure, GCP, and Kubernetes environments, and narrow it down to the handful of security events that matter. Customers all over the globe depend on Lacework to drive revenue, bring products to market faster and safer and consolidate point security solutions into a single platform. Founded in 2015 and headquartered in San Jose, Calif, with offices all over the world, Lacework has raised $600M in funding and is backed by leading investors like Sutter Hill Ventures, Altimeter Capital, Liberty Global Ventures and Snowflake Ventures, among others. The company is in the hyper-growth phase and is being led by an experienced team who collectively have decades of experience taking nascent companies to hyper-scale and building robust & profitable businesses.
 
The Role: We are looking for a Data Scientist to help bootstrap a newly formed team in the Product & Engineering org.  This is a hands-on role that would play a critical role in building the team from the ground up and help shape direction and decisions that are going to directly impact the trajectory of the company. This individual would be a leader in the definition and development of the data science & data engineering ecosystem at Lacework and be an integral part of product  and engineering teams to identify how data science & data engineering can be applied to scale, improve & optimize our products and engineering stack
 

Employ languages and tools like R, SQL, Python and others to drive efficient data exploration and modeling
Build actionable insights and models to help drive critical decisions
In partnership with engineering, product and business teams, build roadmaps & goals and execute against them while balancing speed, accuracy and precision
Actively participate in recruiting other Data Scientists and Data Engineers and mentor new members of the team
Build strong cross functional partnerships
Demonstrate good communication skills and present work to company leadership and at company-wide events
Strive to use readily available, general and scalable methodologies and tools; stay current with latest tools and techniques

Minimum Qualifications

Degree in quantitative field (e.g. Computer Science, Engineering, Mathematics, Statistics, Operations Research or other related field)
4+ years experience doing quantitative analysis including experience with SQL, other programming languages (e.g, Python) or statistical/mathematical software (e.g, R, SAS, MATLAB)
4+ years of experience with statistical and machine learning methods such as forecasting, time series analysis, experimentation, hypothesis testing, classification, clustering, anomaly detection or regression analysis
3+ years experience developing data pipelines and building machine learning models
Ability to deal with ambiguity, drive projects / analyses to conclusion with limited supervision and communicate analysis in a clear, concise and actionable manner

Preferred Qualifications

Advanced degree (Master’s or PhD or equivalent experience) in quantitative field
Experience with cloud platforms like Snowflake, AWS, GCP, etc.
Experience working in Cloud Security or Infrastructure Security
Experience recruiting and mentoring Data Scientists and Data Engineers

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