LexisNexis Risk Solutions is looking to 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
Requirements
- 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
- Experience in classification or mortality model build is a plus
Responsibilities
- 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
- Define scope of a project with support of managers and execute that project independently
- Support the development and training of junior staff
- Support the development of best practices
Other
- 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
- 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
