Principal Data Scientist I

Zinnia is disrupting the insurance industry by delivering innovative technology-driven experiences. We are advancing our tech capabilities and learning to leverage our hordes of data to develop innovative data applications. We are relentless in our drive to reliably deliver outstanding products at scale. We are growing fast, and we can go further faster with experienced, collaborative, challenge-seeking analytics
leaders like yourself.
Our data team serves Zinnia through data engineering, data analysis, and data science. Our goal is to help uncover opportunities and make decisions with data. We partner with all department stakeholders across the company to develop deeper predictors of behavior, develop insights that drive business strategy and build solutions to optimize our internal and external experiences.
In this role, you will…
● Work in a dynamic and innovative company to develop cutting-edge solutions
● Develop machine learning based applications using supervised and unsupervised models using R or Python that optimize and personalize customer experiences or reduce manual effort on our
internal teams through automated decision making
● Develop and support models to enable things such as prescriptive insights, automated decisioning, and insights derived from large audio and text corpus.
● Develop experiments to understand model impact, monitor live model analytics, and manage training and retraining pipelines
● Work with stakeholders to intake complicated business problems and translate them into solvable data science projects.
● Partner with data engineering to take your model from development to deployed infrastructure
● Brainstorm future use cases and contribute to the learning culture of the data science team
● Partner with and mentor other data scientists and data analysts
● Partner with multiple marketing teams, manage multiple projects and help conceptualize applications that directly drive company growth and strategy.
● You will connect machine learning applications to business needs and help facilitate process changes based on algorithmic solution implementation
We’d love to hear from you if…
● You have Data Science experience building and validating machine learning and forecasting models in R or Python
● You have experience in supervised and unsupervised model techniques such as random forest, gradient boosting, support vector machines, k-means and hierarchical clustering, causal models, mixture models and experience in advanced modeling techniques such as reinforcement learning, neural networks, and natural language modeling
● You have experience in delivering natural language projects utilizing techniques such as text summarization, topic modeling, entity extraction, semantic encoding, and valence analysis
● You have experience working in an agile business setting
● You have experience with relational cloud databases like BigQuery and Snowflake and are comfortable working with unstructured datasets such as unstructured text and audio.

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