Arbol is a global climate risk coverage platform and FinTech company offering full-service solutions for any business looking to analyze and mitigate exposure to climate risk. Arbol’s products offer parametric coverage which pays out based on objective data triggers rather than subjective assessment of loss. Arbol’s key differentiator versus traditional InsurTech or climate analytics platforms is the complete ecosystem it has built to address climate risk. This ecosystem includes a massive climate data infrastructure, scalable product development, automated, instant pricing using an artificial intelligence underwriter, blockchain-powered operational efficiencies, and non-traditional risk capacity bringing capital from non-insurance sources. By combining all these factors, Arbol brings scale, transparency, and efficiency to parametric coverage.
Arbol is seeking an experienced Python quantitative developer. The Ideal candidate is someone who has experience working with analysts, researchers and other quantitative developers in commodities or other financial products. This role requires a developer who has implemented models, frameworks and libraries to enable other stakeholders to focus on their own work.
We are looking for an engineer who is capable of task ownership: taking a task, splitting it into pieces, estimating the amount of work, setting expectations, implementing, covering code with meaningful and reasonable tests, and helping others with their development work by reviewing their code and guiding.
What You'll Be Doing
- Build, test, deploy and maintain algorithms for pricing and risk management
- Work with Arbol’s insurance and derivatives teams to perform business-critical analytics
- Build, grow and scale Arbol’s pricing and risk management infrastructure
What You'll Need
- 7+ years of experience with general CS knowledge and tools: version control, design patterns, CI, various testing approaches, coding environment setup on different platforms, package managers
- 7+ years experience using Python
- 5+ years experience in quantitative development
- 4+ years experience using numpy, pandas
- 3+ years in finance (commodities is preferred)
- 3+ years with cloud computing (AWS is preferred)
- Basic math and probability theory knowledge
What's Great to Have
- Experience with ML/DL python frameworks like TensorFlow or PyTorch is a plus
Candidates for this role must be located in the United States.
Interested, but you don’t meet every qualification? Please apply!
Arbol values the perspectives and experience of candidates with non-traditional backgrounds and we encourage you to apply even if you do not meet every requirement.
Accessibility
Arbol is committed to accessibility and inclusivity in the hiring process. As part of this commitment, we strive to provide reasonable accommodations for persons with disabilities to enable them to access the hiring process. If you require an accommodation to apply or interview, please contact [email protected]
Benefits
Arbol is proud to offer its full-time employees competitive compensation and equity in a high-growth startup. Our health benefits include comprehensive health, dental, and vision coverage, and an optional flexible spending account (FSA) to support your health. We offer a 401(k) match to support your future, and 20 days of PTO for you to relax and recharge.
Top Skills
What We Do
Arbolus is changing the way businesses learn and retain knowledge
We believe experience is worth sharing, so we set out to help people with experience share their experience easily with businesses.
Today, Arbolus is the first platform that helps businesses build and work with networks of experts, advisors and freelance consultants. Our product has been a big hit with global consulting firms (e.g. the big four) and Fortune 500 companies who use third parties to inform their business strategy.
Based in London, we are a venture-backed scale-up with offices in Barcelona (our largest), New York and India.
Why Work With Us
Arbolus is a flat hierarchical culture. We encourage innovation from within every part of the company. As a fast growing company, we have multiple opportunities for learning and developing new skills.
Gallery
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