Measured Analytics and Insurance is a high-growth Insurtech based in Salt Lake City, Utah. We're building smarter cyber insurance products designed specifically for the future of digital risk powered by artificial intelligence and machine learning. At Measured, we passionately believe in the power of data to drive better outcomes for our customers.
We are looking for a Data Scientist to play a critical role in our growing Data Science team, building the best-in-class cyber insurance risk modeling technology. The ideal candidate will be responsible for developing advanced analytics and machine learning models across multiple product channels. If you are passionate about transforming data into actionable insights, we want to talk to you.
The things we'd like you to do:
- Partner with business and technical stakeholders across the organization to translate challenging business problems into impactful data science solutions
- Collaborate with data engineers, data stewards, product owners and business users to support projects through the end-to-end data science lifecycle, including data wrangling, exploratory analysis, hypothesis testing, modeling, rapid prototyping, business validation/testing, and operational deployment
- Apply a variety of advanced analytical techniques, including predictive modeling, machine learning, time series analysis, simulation, and optimization
- Leverage a diverse set of large structured and unstructured data to derive meaningful insights and information sets for modeling
- Communicate complex analytical work to a variety of technical and non-technical stakeholders
- Maintain expertise and awareness of emerging data science techniques, technologies, and potential business applications
- Work with the engineering team to integrate risk models with Measured’s cyber-insurance products
- Deliver with a user experience mindset, including the production of visualizations and infographics to distill complex information
- BS/BA in Statistics, Mathematics, Computer Science, Data Science, Engineering or quantitative field; Masters in Data Science is preferred or an additional 3 years of relative experience beyond the minimum requirement may be substituted in lieu of a degree
- Knowledge of statistical and modeling techniques including hypothesis testing, dimensionality reduction, supervised learning (classification and regression), forecasting, and unsupervised clustering
- Some knowledge and experience in scripting and programming with Python, Jupyter notebooks and ML/Data Analytics libraries
- Aptitude for learning and applying new technologies related to Data Science and Data Management
- Working knowledge of Data Engineering tools on AWS such as Glue, Athena, S3
Get in on the ground floor of a new & growing company
Significant career advancement opportunities in an expanding operation.
The chance to have direct input on shaping company strategy and direction
Autonomy while being supported by skilled teammates
Ability to work remotely