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Data Scientist

Resilience

Resilience

Data Science
New York, NY, USA
Posted on Thursday, June 20, 2024
About Us
At Resilience, we’re creating a new category that integrates cybersecurity, cyber insurance, and cyber risk management.
Founded in 2016 by experts from across the highest tiers of the US military and intelligence communities – and built by prominent leaders and innovators from the insurance, technology, and cybersecurity industries – Resilience is rewriting the rules of how cyber risk is assessed, measured, and managed. Our integrated cyber risk solutions connect risk quantification software, cybersecurity experts, and A+ rated cyber insurance, all purpose-built for middle and large organizations.
Guided strongly by our mission and four core values - transparency, excellence, grit, and humility, our culture uniquely blends many different backgrounds, experiences, and skills from across industries and geographies - all focused on helping our clients and partners stay ahead of the bad guys. We are a cybersecurity company, a Cyber and Tech E&O-focused MGA, a fintech startup, and a data science powerhouse, all purposefully built into one.
Resilience is proud to be backed by leading technology investment firms, including General Catalyst, Lightspeed Venture Partners, Intact Ventures, Founders Fund, CRV, and Shield Capital. With headquarters in San Francisco, Resilience’s team is globally dispersed, with offices in New York, Chicago, Baltimore, Los Angeles, Toronto, and London. Resilience offers insurance coverage through its licensed and appointed insurance agents and security services through its expert security team.
Resilience is looking for a Data Science/Machine Learning engineer that will focus on quantifying and communicating risk and mitigation strategies.
You will collaborate closely with our engineering, product, design, and customer-facing teams to develop, maintain, and enhance our risk assessment and quantification capabilities. Your work will involve creating tools and products that drive our core value propositions for partners and clients. With full ownership of your projects and work streams, you will collaborate with internal and external partners, understanding core issues and developing efficient and timely solutions.
This is a hybrid located in one of the following locations: New York, NY or Baltimore, MD.

Responsibilities:

  • Transform complex data and problems into clear and intuitive solutions.
  • Contribute code directly to production systems.
  • Collaborate with a wide range of stakeholders both within the organization and externally to enhance understanding of results and identify areas for improvement.

Qualifications:

  • Extensive knowledge of statistics and machine learning, with a minimum of 5+ years of experience in the field
  • 5 -7 years of engineering/coding skills python is required
  • Experience with software development tools and practices (git, CI/CD systems, etc)
  • Previous experience in customer- facing roles
  • Strong communication skills to collaborate with internal/external stakeholders
  • Experience with Bayesian networks or Bayesian statistics, a plus
  • Master's Degree or higher in a quantitative field is preferred.
What Resilience Offers You
Innovative company culture
Flexible work schedules
Family paid leave
Paid healthcare for employees
401k
Professional development & career advancements
Flexible paid time off
Employee referral bonus
Accommodations and Accessibility
We want to ensure you're able to perform as well as possible in your interview. As part of that, if you have any accessibility-related needs to ensure a comfortable visit, please let us know. We'll do our best to provide reasonable accommodations to suit your working style during your interview and if you join our team.
If you require a reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employee selection process, please direct your inquiries to our Human Resources team at humanresources@cyberresilience.com.