Job Detail
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Job ID 6918
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Job Categories DATA SCIENTIST
Job Description
About the job
About Ethos
Ethos was built to make it faster and easier to get life insurance for the next million families. Our approach blends industry expertise, technology, and the human touch to find you the right policy to protect your loved ones.
We leverage deep technology and data science to streamline the life insurance process, making it more accessible and convenient. Using predictive analytics, we are able to transform a traditionally multi-week process into a modern digital experience for our users that can take just minutes! We’ve issued billions in coverage each month and eliminated the traditional barriers, ushering the industry into the modern age. Our full-stack technology platform is the backbone of family financial health.
We make getting life insurance easier, faster and better for everyone.
Our investors include General Catalyst, Sequoia Capital, Accel Partners, Google Ventures, SoftBank, and the investment vehicles of Jay-Z, Kevin Durant, Robert Downey Jr and others. This year, we were named on CB Insights’ Global Insurtech 50 list and BuiltIn’s Top 100 Midsize Companies in San Francisco. We are scaling quickly and looking for passionate people to protect the next million families!
About The Role
We are seeking a passionate data scientist on our Risk Platform team. Your role will involve harnessing the power of data to optimize our risk assessment procedures, identifying actionable insights from countless data points, and ensuring our platform remains at the forefront of automated underwriting and fraud prevention. This position offers an opportunity to make a significant impact in a fast-growing startup and to introduce innovative solutions within the life insurance sector.
Duties And Responsibilities
- Design, train, validate and deploy models to uncover hidden insights, optimize rule based systems
- Build predictive models for automated underwriting and fraud prevention
- Conduct thorough data analyses to identify patterns, trends and anomalies
- Collaborate closely with the data analytics team, engineer features, leverage domain knowledge, and partner with actuarial experts
- Work closely with product and engineering teams to embed machine learning models into production
- Regularly evaluate the performance of deployed models, ensuring they remain accurate and relevant
- Refine and recalibrate models based on changing data patterns and feedback loops
- Stay updated with the advancements in data science, risk modeling, AI, NLP
- Partner with leadership and product managers to shape the direction of our risk platform to provide data driven recommendations
- Clearly communicate intuition, concepts and potential impact to senior leadership
Qualifications And Skills
- Master’s or PhD in Computer Science, Data Science, or a related field
- 5+ years of hands-on experience in data science or machine learning. Bonus if this experience is in a medical or life insurance
- Deep understanding of various machine learning algorithms and NLP. Bonus if you have demonstrated expertise in deep learning
- Proven ability in designing, building and productionizing machine learning models in real world scenarios
- Strong expertise in Python and in machine learning libraries/frameworks such as TensorFlow, PyTorch, scikit-learn, pandas etc.
- Hands on experience with sagemaker and ability to independently deploy a model
- Exceptional ability to grasp domain specific nuances quickly. Bonus if there is demonstrated proficiency in applying machine learning to medical or life insurance domains
- Collaborative mindset, eagerness to learn and work with cross-functional teams
- Comfortable in a fast-paced startup environment
