Do you have experience applying and integrating statistical, mathematical, predictive modeling and business analysis skills to manage and manipulate complex, high-volume data from a variety of sources?
Enjoy communicating insights to both internal and external stakeholders in formal and informal settings?
This may be the role for you!
About the Business:
LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within our Business Services vertical, we offer a multitude of solutions focused on helping businesses of all sizes drive higher revenue growth, maximize operational efficiencies, and improve customer experience. Our solutions help our customers solve difficult problems in the areas of Anti-Money Laundering/Counter Terrorist Financing, Identity Authentication & Verification, Fraud and Credit Risk mitigation and Customer Data Management. You can learn more about LexisNexis Risk at the link below, https://risk.lexisnexis.com
About the team:
Our team conducts ad-hoc analyses for internal and external customers using complex data assets, analyzes customer trends and market shifts to support senior leadership decisions, and defines, standardizes, and maintains metric calculations for communications
About the role:
A Senior Data Scientist I should be able to define scope of a project with support of managers and execute that project independently. Individuals in this role can also support the development and training of junior staff. Senior Data Scientist I should be self-sufficient in executing basic methods, and work within their teams to execute increasingly sophisticated approaches to deliver outcomes. They should also support the development of best practices.
Responsibilities
Requires specialized depth and/or breadth of expertise in Life Insurance
Interpret business plays to recommend (and execute) an analytic plan to supervisor and/or client
Summarize and communicate conclusions and solutions to analytic and non-analytic stakeholders
Solves complex problems; takes a broad perspective to identify innovative solutions
Works independently, with guidance in only the most complex situations
Requirements:
Bachelor’s degree in a quantitative field such as Statistics, Applied Math, Computer Science or a related quantitative field with a strong GPA (>3.2). Master’s degree in Actuarial Science, Statistics, or Data Science is preferred.
Proven work experience in data analysis. Proficiency in working with relational databases/query languages (e.g., MySQL, Spark SQL). Experience in matching, merging, and manipulating large data sets using a parallel programming language (e.g. PySpark, ECL) is preferred.
Strong programming skills in Python and/or R is a must.
Deep understanding of mathematical and statistical modeling. Ability to develop hypothesis and test and deploy complex machine learning models in production. Has experience in classification or mortality model build is a plus.
Strong oral and written communication skills, including the ability to describe analytical results to non-statistical audiences
Strong ability to lead projects, develop project plans, communicate project progress, and share modeling/analysis results with business partners.
Comfortable working in a fast-paced environment.
ASA and/or FSA certification is a plus.
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