About Us 
Britive delivers a leading cloud-native security solution built for the most demanding cloud-forward enterprises. We were founded by security industry veterans with a track record as successful entrepreneurs. Our platform empowers cloud infrastructure and security teams with a dynamic and intelligent privilege administration technology for multi-cloud environments and helps minimize the risks of cloud security breaches and operational disruptions. 

We launched our platform less than a year ago and already count several large and Fortune 500 enterprises as customers, including a global automaker, a top retail brand, a national healthcare provider, and a multi-national communications company. Our patent-pending technology has been favorably reviewed by leading analysts at Gartner, Forrester, TechVision, etc. and we are backed by top-tier VCs and prominent angel investors! 

About You 
You are a passionate Principal Data Scientist who wants to who wants to drive business results with your data-based insights. You have a strong data science and cybersecurity background and understand the use of a variety of data mining and data analysis methods to build and implement models, algorithms, and simulations for security platforms. From day one, you must be able to hit the ground running and bring all your experience to the team to ensure our business stays ahead of the industry. You will take the lead to provide strategic direction on large scale business problems. Most importantly, you have a positive “can do” attitude and a passion for delivering technical solutions in a fast-paced startup environment. 

Your Impact 

Key Responsibilities: 

• Lead and guide a data science program to help understand how the wealth of security data can drive insights into weaknesses, threats, and opportunities.  
• Use analytical rigor and statistical methods, programming, data modeling, simulation, and advanced mathematics to analyze large amounts of data, recognizing patterns, identifying opportunities, posing business questions, and making valuable discoveries. 
• Identify/develop appropriate machine learning/data mining/text mining techniques to enable better business outcomes. 
• Understand and analyze data sources including sampling biases, accuracy, and coverage. 
• Break apart problems scientifically, providing insight into your recommendations and findings to both technical and non-technical partners. 
• Research new ways for modeling and predictive behavior for large scale projects. 
• Generate and test hypotheses, designing experiments to answer targeted questions of advanced complexity. 
• Document projects including business objective, data gathering and processes, leading approaches, final algorithm, and detailed set of results and analytical metrics. 
• Validate score performance. 
• Document and present model process and performance. 

What will you need? 

Required Skills: 

• Prior experience in performing the same role in a SaaS security product company.  
• Minimum 10 years of relevant work experience in similar roles. 
• Advanced degree in Machine Learning, Computer Science, Electrical Engineering, Physics, Statistics, Applied Math, or other quantitative fields. 
• Highly technical with both tactical and strategic capabilities.  
• Hands-on experience implementing machine learning and security intelligence solutions. 
• Proven track record in modifying and applying advanced algorithms to address practical problems. 
• Deep understanding of algorithms, machine learning and data science.  
• Confident interacting with business peers to understand and identify use case, with a strong ability to articulate solutions and present them to business partners. 
• Sound knowledge of security in Cloud platforms such as AWS, GCP, Azure. 
• Strong coding skills in one of the following: Python, R, or PySpark. 
• Experience with Hadoop and NoSQL or related technologies. 
• Knowledge of NLP/Text mining techniques and related open source tools.  
• Outstanding collaboration and communication skills. Ability to effectively collaborate with distributed team. 
• Understand and practice agile development methodology. 

Nice to Have: 

• Understanding of DevOps, microservices architecture and container/Docker technologies.