Data Scientist

RELX • Alpharetta, GA

22d • $95,300 - $158,800

About The Position

LexisNexis Risk Solutions is seeking a Sr. Data Scientist I with strong expertise in statistics/modeling and machine learning to join their Auto Insurance Rating Analytics team. This role is crucial for new product innovation, model development, generating actionable insights, and collaborating with Vertical and Product teams to design and implement cutting-edge solutions for the insurance market. The ideal candidate will be able to define project scope with managerial support, execute projects independently, and potentially mentor junior staff. They should be self-sufficient in basic methods and work collaboratively on more sophisticated approaches, contributing to best practices. The role involves developing, analyzing, and modeling various types of organizational data to quantify competitive performance, evaluate operational changes, and design new methodologies. It also requires analyzing data to recommend solutions for complex problems, developing innovative strategies, and modeling the impact of changes. The position demands the application of statistical, mathematical, predictive modeling, and business analysis skills to manage and manipulate complex, high-volume data from diverse sources. The role requires conceptual and practical expertise in data science, knowledge of best practices and how they integrate with other functions, awareness of the competition, and an understanding of market differentiators. While not a formal leadership role, there is an expectation to occasionally lead small project teams and provide informal guidance to junior staff. Problem resolution typically involves using existing solutions, and the work is performed with minimal guidance. Interpersonal skills are important for explaining complex information, and the role involves modeling auto insurance risk, particularly using credit-based data sources and GLM techniques, as well as supporting existing models.

Requirements

• Bachelor’s degree in Mathematics, Statistics, Computer Science, Data Science, or other quantitative discipline (or equivalent years of experience)
• 3+ years demonstrated experience in data manipulation and various AI/ML methodologies, preferably in applications using credit data for insurance or financial services
• Strong expertise in one or more of the following: R, Python, SQL, or equivalent analytic software
• Experience manipulating and merging multiple large data sets in a distributed computing environment
• Solid understanding of ML techniques, including hypothesis testing, sample design, model development (linear and non-linear models), validation of machine learning models
• Strong programming skills in Python and/or R, with extensive experience with their standard data manipulation and ML packages (pandas, scikit-learn, NumPy, XGBoost, PyTorch in Python and rpart, party, caret in R) and/or Scala
• Strong ability as a self-starter to learn new technologies (Pyspark, ECL, Azure/AWS ML Services) and to share cross-functional knowledge across the teams

Nice To Haves

• Master’s/Ph.D. degree preferred
• Actuarial experience/certification also preferred
• Python experience required
• Cloud experience preferred

Responsibilities

• Developing, analyzing, and modeling operational, economic, management, accounting and other organizational data to quantify the competitive performance of business segments, evaluate potential operational changes, and design new approaches and methodologies
• Analyzing organizational data to recommend solutions to new and complex problems, developing innovative strategies, quantifying the competitive performance of the organization's operations and/or markets; modeling and evaluating the potential impact of changes
• Applying and integrating statistical, mathematical, predictive modeling and business analysis skills to manage and manipulate complex high-volume data from a variety of sources
• Models auto insurance risk, particularly in the context of credit-based data sources, generally using GLM techniques
• Supports existing models
• Develops, analyzes and models operational, economic, management, accounting and other organizational data to quantify the competitive performance of business segments, evaluate potential operational changes, and design new approaches and methodologies
• Analyzes organizational data to recommend solutions to new and complex problems, develops innovative strategies, quantifies the competitive performance of the organization's operations and/or markets; models and evaluates the potential impact of changes
• Applies and integrates statistical, mathematical, predictive modeling and business analysis skills to manage and manipulate complex high-volume data from a variety of sources

Benefits

• This job is eligible for an annual incentive bonus.
• country specific benefits

What This Job Offers

• Job Type: Full-time
• Career Level: Senior