Data Scientist

The Role:

Entera is looking for a Data Scientist to join our growing data team. The primary function of this role is to work with our Data Engineering team to build, deploy, and maintain production-ready machine learning models and statistical analyses. You'll work with the support of best-in-class developers who will surface your work to both internal users in our reporting systems, as well as our customer facing frontend product, in the form of dynamic reports, data visualizations, and interactive tools.

We are a tight data-driven group of technology experts that value measurable and reproducible statistical models that scale well in production environments, and ultimately the business value that can be extracted from those models. You’ll contribute to many areas of our technical stack and have autonomy to work on various types of interesting and challenging data science problems. You will be coming in at the ground floor of this effort and will play a large role in shaping our data science culture.

Successful candidates will thrive in Entera’s unique operating environment and culture: high-growth, innovative, lean, and values-driven. As such, successful candidates must be highly capable in each of the following dimensions (among others): resourcefulness, adaptability, curiosity, analytical thinking/problem solving, proactivity, collaboration, technological savvy, and operating in a dynamic environment.

What You’ll Do:

• Use Python, SQL, and R to statistically model and analyze large sets of data
• Perform feature engineering across various sets of real estate, economic, and demographic data
• Build machine learning models and statistical analyses, and productionize them for use over structured and sensible APIs using Python
• Iterate in an agile development workflow and use version control systems (Git) to manage model validation, measurement, and continuous improvement
• Utilize distributed compute frameworks like Spark or Dask to process large datasets and train models
• Work with our Data Engineering and DevOps teams to deploy and maintain models and CI pipelines
• Write and maintain technical documentation for the data models you produce, and be able to champion your approach and communicate results to the business in an easily interpretable way
• Help to define and improve our internal standards for style, maintainability, and best practices for a high-scale data infrastructure
• Partner with other teams to accomplish data science efforts around our Underwriting, Brokerage, Marketing, and Sales processes
• Evangelize a culture of 'data-first', and seek data-driven feedback in all that you do

Requirements:

• MS or PhD in Computer Science, Mathematics, Statistics, Physics, Economics, or similar hard-science.
• 5+ years hands-on experience in Data + Analytics at growing product-driven tech companies
• Minimum 3 years experience building, deploying, and maintaining machine learning models in production environments
• Experience with Python / R libraries for data manipulation and statistical modeling such as: Numpy, Pandas, dplyr, scikit-learn, Tensorflow, PyTorch, Caret
• Deep interest in statistical learning, computational topology, geometry, and higher order maths
• Expertise with Spark, Dask, or similar distributed compute frameworks
• Working knowledge of AWS
• Experience using and working with large scale data pipelines
• Data-driven in all aspects of your life
• Nice to have:
• Familiarity with SQL and data warehousing systems like Snowflake, BigQuery, RedShift
• Familiarity with data orchestration systems like Airflow or Prefect
• Working knowledge of a Python web framework like Flask