Data Scientist at Bestow

ABOUT BESTOW

Bestow is the leading digital platform for life insurance. As both a direct-to-consumer destination and an infrastructure provider, Bestow is on a mission to make life insurance accessible to millions of underserved families. 

We strive for work-life balance and believe happy employees make for better experiences and happier customers.  It’s a model that helped us land on Forbes’ Best Startup Employers 2021 and 2022 lists!


Open to Dallas, Austin, or (US) Remote 
#LI-Remote


Data Science at Bestow is a rapidly evolving team with a diverse set of problems to solve. We analyze and manipulate massive datasets, build algorithmic models to make predictions, and optimize decision-making by reinforcing choices with data.   At Bestow you will be working on all aspects of the data science pipeline from project requirements to production deployment. We use cutting-edge machine learning and data warehouse technologies to create a cohesive environment for experimentation and analysis. In addition to the standard suite of analysis tools involved in data science projects, you will be engineering and developing infrastructure and code to facilitate everything from training models to serving those models in production and integrating your products with those of other teams. Communicating results effectively to both technical and non-technical audiences is a skill all of our data scientists must possess as we work closely with the entire organization.  


Challenges On Which You Can Expect to Work:  At Bestow we leverage data to build the best customer experience in the term life insurance industry. You will work on building attribution, propensity, and response models to gain deep knowledge and comprehensive understanding of the customer and work with the marketing teams to run better targeting, funnel optimization, and audience selection experiments to finally drive towards automation of campaigns. As a leader in the digital life insurance space Bestow is driving innovations around the way risk and pricing are currently modeled in the industry. You will be working alongside the underwriting and actuarial teams on cutting-edge work building an underwriting engine driven by Machine Learning. This will require out-of-the-box thinking around using new data sources available to us including health data to create new ways of modeling mortality, eligibility, and pricing.  


Data Science and Machine Learning Infrastructure  Developing and optimizing our Data Science environment is a powerful way for us to enable our team to work efficiently. This also helps us integrate well with other teams by having a secure and standardized way to work and gives us a basis on which to discuss our problems and solutions. We currently use Kubeflow and its associated components. We leverage Google BigQuery as our data warehouse. We use Jupyter notebooks and Python code to compose sophisticated machine learning pipelines and experiments. Collaborate across teams to identify project requirements and metrics; Work closely with Data Engineering team who perform data analysis and cleaning using a host of ETL tools; Train and tweak machine learning models to make predictions; Use statistical evaluation techniques to refine models over time based on performance metrics; Production engineering - after a model is developed, we see it through to production; Communicate with the organization by interpreting models and results for non-technical audiences    


Analytics  We work closely with analytics teams to enable them to do their work effectively as well as refine their insights into predictive analytics through machine learning. This involves acquiring knowledge and insight from various domains and refining it into high-level motivation for decisions within the organization or models to increase our products’ efficacy. Our Data Science team follows agile methodology as all our other engineering teams.



About You: 

3+ years of data science experience
Experience with marketing work (propensity models, attribution models, response models, audience selection, and retargeting) 
Programming and Statistics/Mathematics experience
Professional experience with a variety of machine learning algorithms
You like building and evaluating experiments under statistical rigor
Solid Python 3 and Software Engineering principles
Experience with notebook and analytical environments (Jupyter, R)
Clear, concise written and verbal communication
Desire and willingness to learn
Display initiative and autonomy as well as cross-team collaboration



It would be great if you had: 

Experience with Kubernetes Cluster Orchestration & Management Framework 
Experience deploying models into production and managing uptime and performance
Experience in creating software products like APIs and  web applications



Total Rewards: 

Generous compensation package
Stock options
Flexible schedule and work/life balance
100% company-paid health, dental, and vision insurance
Choose your computer setup (13” or 16” MacBook Pro)
Team building events and activities


We value diversity at Bestow. We hire, recruit, and promote without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, pregnancy or maternity, veteran status, or any other status protected by applicable law. We understand the importance of creating a safe and comfortable work environment and encourage individualism and authenticity in every member of our team.