Security Data Scientist

Arctic Wolf, with its unicorn valuation, is the leader in security operations in an exciting and fast-growing industry—cybersecurity. We have won countless awards for our excellence in security operations and remain dedicated to providing an industry-leading customer and employee experience.

Our mission is simple: End Cyber Risk. We’re looking for a Security Data Scientist to be a part of making this happen.

About the Role

Data is a critical part of Arctic Wolf Network’s mission to solve cyber risk, where we process and analyze hundreds of billions of events every day to look for malicious and risky behaviour. Furthermore, we’re geeks at heart and are passionate about data and solving cybersecurity problems for our customers. The AI & Data Science team works on analyzing Arctic Wolf’s product platforms, internal business challenges, and customer pain points to develop new products and features for our customers.

As a Security Data Scientist on the AI & Data Science team you will be responsible for developing data-driven solutions leveraging cutting-edge advanced analytics techniques. This involves working closely with engineering, product, operations, and other teams to understand the most important technical and business analytics needs to drive security-centric analytics outcomes. A successful candidate is self-motivated with a passion for excellence and attention to detail.

As a Security Data Scientist at Arctic Wolf, you will…

  • Analyze and correlate complex data from multiple sources.
  • Perform exploratory data analysis to gain deeper understanding of the data.
  • Work with stakeholders, including domain experts and product, to understand use cases and domain-specific problems and identify opportunities for applying machine learning to drive outcomes.
  • Develop tools and algorithms for generating synthetic data sets.
  • Define KPIs to measure model performance.
  • Develop and test statistical and machine learning models for efficacy and operational impact.
  • Write production quality code and work with other software engineering teams to deploy models into production.
  • Support deployed models as a subject matter expert.
  • Be creative and engineer novel features and methods to push beyond our current capabilities.

We are looking for someone who has…

  • Proven track record in the research, data science and engineering around building and shipping machine learning or statistical models that scale to high volumes of data (billions of data points).
  • Proficiency with Python and SQL.
  • Experience using key ML libraries including scikit-learn, tensorflow, pytorch, sparkml.
  • Experience with data fusion and data cleansing techniques for creating labelled data sets.
  • Experience with developing synthetic data sets using generative and statistical modelling techniques.
  • Understanding of classical ML and DNN modelling techniques for supervised and unsupervised learning and sequence modelling.
  • Understanding of 3 of either PGMs, RL, GNN, statistical modelling, or time series modelling.
  • Understanding of ensembles and multi modal machine learning techniques to solve complex problems.
  • Familiarity of large-scale distributed systems and related technologies such as Spark, Elasticsearch, Kubernetes, etc. is a plus.
  • Familiarity with cloud platforms (we use AWS here) and automation technologies (e.g., Kubernetes, Jenkins, Chef, etc.) is a plus.
  • Familiarity with the information/cyber security domain is a plus.

About Arctic Wolf

At Arctic Wolf we’re cultivating a collaborative and productive work environment that welcomes a diversity of backgrounds, cultures, and ideas to make our teams even stronger as we grow globally. We’ve been named one of the 50 Most Innovative Companies in the world for 2022 (Fast Company)—and the 2nd Most Innovative Security Company. We have won countless awards for our excellence in security operations and remain dedicated to providing an industry-leading customer and employee experience including:

  • Top Workday USA (2021-2024)
  • Great Place to Work (2022-2024) & Best Workplaces for Women (2024) in Canada
  • Best Workplaces in Tech & For Women in the UK (2023)
  • Top Company by Kununu in Germany (2024)

Our Values

Arctic Wolf recognizes that success comes from delighting our customers, so we work together to ensure that happens every day. We believe in diversity and inclusion, and truly value the unique qualities and unique perspectives all employees bring to the organization. And we appreciate that—by protecting people’s and organizations’ sensitive data and seeking to end cyber risk— we get to work in an industry that is fundamental to the greater good. 

We celebrate unique perspectives by creating a platform for all voices to be heard through our Pack Unity program. We encourage all employees to join or create a new alliance. See more about our Pack Unity here.  

Arctic Wolf is an Equal Opportunity Employer and considers applicants for employment without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics, or any other basis forbidden under federal, provincial, or local law. Arctic Wolf is committed to fostering a welcoming, accessible, respectful, and inclusive environment ensuring equal access and participation for people with disabilities. As such, we strive to make our entire employee experience as accessible as possible and provide accommodations as required for candidates and employees with disabilities and/or other specific needs where possible. Please let us know if you require any accommodations by emailing recruiting@arcticwolf.com.

Security Requirements

  • Conducts duties and responsibilities in accordance with AWN’s Information Security policies, standards, processes, and controls to protect the confidentiality, integrity and availability of AWN business information (in accordance with our employee handbook and corporate policies).
  • Background checks are required for this position.

Location

Bengaluru

Job Overview
Job Posted:
8 months ago
Job Expires:
Job Type
Full Time

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