Lead Data Scientist

Compensation

: $115,435.00 - $200,310.00 /year *

Employment Type

: Full-Time

Industry

: Information Technology



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Responsibilities

  • Independently leads data analysis and modeling projects from project/sample design, business review meetings with internal clients deriving requirements/deliverables, exploration, reception and processing of data, performing analyses and modeling to final reports/presentations, communication of results and implementation support.
  • Demonstrates to stakeholders how analytics can be implemented to maximize business benefits. Provides support, which includes strategic consulting, needs assessments, project scoping and the preparation/presentation of analytical proposals.
  • Utilizes advanced statistical and learning methods to create high-performing models and creative analyses to address business objectives and client needs.
  • Drives the use of data-based decision making and Analytics by active internal partnership management, discovering business opportunity and creating business value by executing on high-priority projects.
  • Tests new statistical analysis methods, software and data sources for continual improvement of quantitative solutions. Shares knowledge within Analytics group.
  • Proactively and effectively communicates in various verbal and written formats with internal stakeholders on product design, data specification, model implementations, with partners on collaboration ideas and specifics, with clients and account teams on project/test results, opportunities, questions. Resolves problems and removes obstacles to timely and high-quality project completion.
  • Creates project milestone plans to ensure projects are completed on time and within budget. Provides high quality ongoing customer support; answering questions, resolving problems and building solutions.
  • Actively contributes to analytics strategy by contributing ideas, preparing presentation material for internal stakeholders, and product design/business case materials for leadership.
  • Follows industry trends in insurance and related data/analytics processes and businesses. Functions as the analytics expert in meetings with other internal areas and external vendors. Actively participates in proof of concept tests of new data, software and technologies.
  • Assures compliance with regulatory and privacy requirements during design and implementation of modeling and analysis projects.
  • Travels to events and vendor meetings as needed (< 10%).

Required Qualifications
  • Graduate-level degree with concentration in a quantitative discipline such as statistics, computer science, mathematics, economics, or operations research
  • 5+ years of data science experience using large and complex datasets in a business setting. Digital/web marketing analytics experience preferred.
  • Strong expertise in statistical and machine learning techniques such as linear regression, logistic regression, survival analysis, GLM, tree models (Random Forests, GBM), cluster analysis, principal components, feature creation
  • Proven ability to execute end-to-end modeling lifecycle
  • Expertise in design-of-experiments and statistical inference
  • Strong expertise in regularization (Ridge, Lasso, elastic nets), feature engineering and selection (transformation, high level categorical reduction, splines, etc.) and validation (hold-outs, CV, bootstrap)
  • Substantial programming experience with several of the following: R, Python, H2O, SPARK, SQL. Experience with Hadoop toolkit. Exposure to Git.
  • Proven ability to effectively manage own time while working on several time-sensitive projects and competing priorities in a dynamic business environment while maintaining strong, productive relationships with internal stakeholders and external partners
  • Strong verbal and written communications skills, listening and teamwork skills, and effective presentation skills. This is absolutely essential since you will have a lot of exposure to different internal groups (data, IT, multiple groups within business) as well as third-party data partners.
  • Proficiency in creating effective and visually appealing presentations
  • Experience with data visualization tools (e.g. R Shiny, Spotfire, Tableau) is a plus
  • People management experience a plus

Associated topics: data analytic, data architect, data center, data integrity, data manager, data scientist, data warehousing, etl, hbase, mongo database administrator * The salary listed in the header is an estimate based on salary data for similar jobs in the same area. Salary or compensation data found in the job description is accurate.

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