Lead Data Scientist

  • 37980
  • Non-Life - Data Science
  • |
  • New York, United States
  • |
  • Aug 17, 2020
  • Incorporate new, cutting edge business intelligence, machine learning, and alternative data practices into wider organization to drive efficiencies and generate revenue
  • Own the full stack execution of data science projects from data wrangling, model development, presentation, measurement to deployment
  • Work with data engineers to produce fully productionized pipelines including data ingestion, cleaning, feature engineering and model training/prediction.
  • Conduct research and analysis into reinsurance and advisory products to augment industry-standard models and develop new market offerings for the company’s clients
  • Establish and maintain strong relationships with internal team members and external clients when possible
  • Monitor performance of data products and respond to internal inquiries regarding their maintenance
  • Evangelize data science techniques and best practices throughout analytics and engineering teams
  • Keep up-to-date on the latest trends and innovation in data science tools and techniques and how these trends apply to the company’s business and data strategy
  • Own the implementation for data products on the team’s roadmap
  • Development data science and engineering talent within the team
  • Support the hiring of technical and business talent
  • Partner with the team product manager to manage technical communications with stakeholders
  • Collaborate with the product manager to establish sprint backlogs, stories and estimation
  • 3-5 years of experience as a data scientist or in equivalent quantitative engineering role
  • Significant experience with Python (pandas, sklearn), Spark (RDDs, dataframes), machine learning algorithms and libraries (TensorFlow, PyTorch), SQL
  • Must be able to produce production level code and familiar with engineering best practices (e.g. unit testing, code reviews)
  • Experience acquiring and organizing data in cloud and on-premises environments
  • Bachelor’s or Master’s Degree in data science, computer science or related quantitative field such as applied mathematics, statistics, engineering or operations research
  • Experience working in an Agile environment to facilitate the quick and effective fulfillment of group goals
  • Good interpersonal skills for establishing and maintaining good internal relationships, working well as part of a team and for presentations and discussions
  • Strong analytical skills and intellectual curiosity as demonstrated through academic experience or work assignments
  • Ability to communicate technical concepts to non-technical audience
  • Excellent verbal and writing skills for complex communications with colleagues at all levels of the organization
  • Good ability to prioritize workload according to volume, urgency, etc. and to deliver on required projects in a timely fashion
  • Desire to take ownership of proposed and assigned tasks and to seek assistance when needed
  • Ability to thrive in ambiguity, and drive technical focus in directions of high business value
  • Experience with machine vision and extracting structured information from images, multimedia, and other unstructured file formats (CSS)
  • Prior experience in relevant insurance/reinsurance field performing analytic analysis or experience in building model/software products for financial or insurance industry
  • Familiarity with modern data productivity frameworks and their alternatives such as Databricks, DataRobot and Alteryx
  • Significant experience with natural language processing techniques ranging from topic classification to sentiment analysis