FireEye is an intelligence-led security company. Working as a seamless, scalable extension of customer security operations, FireEye offers a single platform that blends innovative security technologies, nation-state grade threat intelligence, and world-renowned Mandiant consulting. With this approach, FireEye eliminates the complexity and burden of cybersecurity for organizations struggling to prepare for, prevent, and respond to cyber-attacks. FireEye has over 9,000 customers across 103 countries, including more than 50 percent of the Forbes Global 2000.
If you dream of a job working in a field where all the hard problems are solved and you get to re-use previous research to get your job done, you need not apply. If, however, you are someone who wants to tackle problems that truly are on the cutting edge, then we encourage you to keep reading.
Data Science is an emerging field within cybersecurity. FireEye, given its deep expertise and comprehensive view on the advanced threat landscape, is uniquely positioned to enable data scientists to have a major impact within our industry, company, and across our customer base. Detecting security breaches using machine learning and data analytics is an unsolved problem (this is not handwriting recognition folks) and has huge potential.
If you are someone who wants to be on the cutting edge of a high profile industry, who wants to make an impact by pushing both fields of data science and cybersecurity forward, you may be the perfect candidate to help us on our mission.
In this role, you will design and implement software to support data science projects, including backend processing, data ingestion, training and evaluation pipelines.
What you will do:
Develop, and manage data systems to ingest and process data at massive scale
Contribute towards the architecture and design of software solutions for long-term storage and retrieval, including managing large-scale datasets
Work with data scientists to productize ML models and assist product teams with ML model releases into end products
Collect requirements, design, and build backend components and tools to serve ML models, receive feedback, and generate model statistics
Identify and implement data exploration technologies. Create dashboards and implement analytical tools for exploration
Contribute to the evolution of coding and design practices within the organization, implementing ETL processes and building data pipelines
Review code base commits and contribute to the growth of team members
Ability to work in an iterative, agile development environment
Strong experience developing in Python 3
Experience developing reliable distributed systems
Deep knowledge of AWS services and associated tools
Strong knowledge of a variety of operating systems, networking fundamentals, software design and programming best practices
Experience with the use of a wide array of algorithms and data structures
Deep understanding and experience of going through the entire life cycle of building software platforms and products
Experience in schema design
Experience developing in at least 1 of the following: C, Go or Java
Experience with RDBMS, such as PostgreSQL or MySQL, as well as NoSQL
Experience with Kubernetes and Docker
Experience deploying products in AWS
- Ability to pick up, work with and explore new analytical tools
- Strong experience with DevOps practices and common tooling
- Strong communication skills.
- Ability to work with loosely defined requirements.