- Onboarding new customers' into our model-training process.
- Improving and extending our ML models to predict policy cash flow over time.
- Enhancing our automated model monitoring to watch for things such as performance degradation and data drift.
- Pursuing opportunities for further automation of our training / evaluation pipelines by enabling customers to seamlessly integrate into our systems.
- Creating and automating additional data analytics and reports we offer our customers on top of their application and claims data.
- Researching additional lines of insurance to help drive our expansion roadmap.
- Fully cloud-based on AWS
- SageMaker for ML workflows - Data exploration, processing, model prototyping, training, management, and serving
- Airflow for job orchestration
- Amazon API gateway for exposing public APIs
- AWS Lambda Functions (Python) for general purpose utility functions
- ML and data processing code in Python (Lightgbm, Pandas, scikit-learn)
- Python for backend services code
- Infra managed by Terraform
- 5 People
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Machine Learning Engineer - San Francisco, United States - Soteris
Description
[Full Time] Machine Learning Engineer at Soteris (United States) | BEAMSTART JobsMachine Learning Engineer
Soteris United States
Date Posted
06 Dec, 2022
Work Location
San Francisco, United States
Salary Offered
$150000 — $210000 yearly
Job Type
Full Time
Experience Required
1+ years
Remote Work
Yes
Stock Options
No
Vacancies
1 available
ABOUT SOTERIS:
Soteris is a YC-backed, seed-stage, profitable company building a machine-learning-based insurance pricing platform.
Earlier this year, we finished a 15-month pilot with an auto insurer that resulted in almost tripling their policy profitability.
As a result, in less than a year, our revenue has tripled.Additionally, in the last month we've signed a number of new customers up for pilots, which has the potential to quadruple our revenue further from here.
The opportunity per customer is so large because our ML tech integrates directly into the critical path of their business (pricing the risk).
There's $750B of insurance policies written in the US every year, yet insurance companies generally lack the sophistication necessary to price insurance individually.
Instead, they generally place people into a small number of discrete buckets that dictates the price charged. Our ML platform allows them to calculate a highly customized price instead. The team is under 5 people, remote across the US, and growing.You would be our second ML engineer and would be responsible for building out both the ML infrastructure we use to train insurance-pricing algorithms from application + claims data, as well as the models themselves.
WHAT YOU'LL DO:
As an ML Engineer at Soteris, you will get to work on many facets of the ML functionality that drives business value for our customers.
OUR STACK:
Here's a look at our current tech stack.
Experience with these is ideal, but it's not required so long as you have the ability and desire to pick them up quickly:
ABOUT YOU:
Overall, the needed skill set is approximately 60% statistician, 30% engineer, and 10% business strategist. You probably think of yourself as a statistician first and a software engineer second.
There are no specific requirements per se - if you're interested in the role and feel you have an ability to do the job described above, we'd love to see an application from you.
If this seems interesting to you and you'd like to find out more, please reach out by clicking the Apply buttonAbout Soteris
Building a first-of-its-kind data platform for commercial insurance.
Company Size:
2018
Country:
United States
Company Status:
Actively Hiring Looking for Partners Looking for Clients Raising Funds
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