Description
About Reserv
Reserv is an insurtech creating and incubating cutting-edge AI and automation technology to bring efficiency and simplicity to claims. Founded by insurtech veterans with deep experience in SaaS and digital claims, Reserv is venture-backed by Bain Capital and Altai Ventures and began operations in May 2022. We are focused on automating highly manual tasks to tackle long-standing problems in claims and set a new standard for TPAs, insurance technology providers, and adjusters alike.
We have ambitious (but attainable!) goals and need people who can work in an evolving environment. If building a leading TPA and the prospect of tackling the long-standing challenges of the claims role sounds exciting, we can’t wait to meet you.
Who you are
As a Senior Machine Learning Engineer at Reserv, you will define our technological trajectory and drive growth for years to come. You will play a crucial role in our data science team, collaborating directly with customers to develop AI and machine learning solutions that address critical operational inefficiencies. This position is ideal for a data scientist with a solid foundation in software engineering, predictive modeling, and an innovative mindset ready to shape the future of our technology.
What we need
- Develop and integrate AI models and machine learning solutions using our tech stack: Python, AWS (including Bedrock, SageMaker), Docker, Postgres, and Ruby on Rails.
- Collaborate with product management and operations to identify and prioritize machine learning opportunities.
- Design, test, and deploy scalable machine learning architectures that facilitate rapid iteration, secure deployment, and user-friendly access.
- Guide the creation and implementation of both heuristic and complex machine learning models, adhering to the principle of "Occam’s Razor."
- Mentor junior data scientists and support developers at customer companies.
- Continuously deploy code from day one, influencing and enhancing our engineering culture.
- Communicate technical ideas and specifications clearly and precisely.
- Engage with cross-functional teams including product ops, design, and sales as our product and engineering teams expand.
Requirements
- 8+ years of experience as a data scientist with a robust portfolio demonstrating high-quality product delivery.
- Experience in running end-to-end experiments, including setting up datasets, developing controls, conducting hypothesis tests, running ablation studies, and rigorously evaluating outcomes.
- Expertise in Python and libraries such as Pandas, LangChain, NumPy, Scikit-Learn, TensorFlow, and/or PyTorch.
- Strong software engineering foundation with a commitment to delivering high-quality, maintainable, and well-tested code
- Proven ability to stay updated with state-of-the-art techniques through continuous research and application.
- Strong ability to prioritize customer requirements and adapt quickly to evolving project scopes.
- Passionate about creating intuitive technology solutions and a continuous desire to learn and take on new challenges.
Benefits
- Generous health-insurance package with nationwide coverage, vision, & dental
- 401(k) retirement plan with employer matching
- Unlimited vacation time with minimum time-off – we want our employees fresh, healthy, happy, and energized!
- Generous family leave policy
- Work from anywhere to facilitate your work life balance paired with frequent, regular corporate retreats to build team cohesion, reinforce culture, and have fun
- Your choice of Windows or Apple laptop, large second monitor, and other quality-of-life equipment you may want. Technology is something that should make your life easier, not harder!
At Reserv, we value diversity in backgrounds, perspectives, and life experiences and believe that diversity in viewpoints and critical thinking drives innovation, first-principles thinking, and success. We welcome applicants from all backgrounds and encourage those from all walks of life to apply. If you believe you are a good fit for this role, we would love to hear from you!
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