Data Scientist

RELX; Alpharetta (GA); On-site; USD 95,000 - 159,000; Full time

Job summary

LexisNexis Risk Solutions is seeking a Senior Data Scientist I to join the Auto Insurance Rating Analytics team. You will define project scope, execute independently, and mentor junior staff while delivering advanced modeling and insights.

Strong Python/R skills and experience with ML are essential. You will work with cross-functional teams to design innovative solutions that enhance risk assessment and business decision-making, using cloud platforms and scalable analytics.

Qualifications

• Bachelor’s or higher in a quantitative field; actuarial experience is a plus.
• 3+ years of data manipulation and AI/ML methods with credit data or similar.
• Strong in Python and/or R, SQL, and ML package ecosystems.
• Experience with distributed computing and large data sets.
• Solid understanding of ML techniques and model validation.

Responsibilities

• Develop, analyze, and model data to quantify business performance and risks.
• Evaluate operational changes and design new analytics approaches.
• Apply statistical and predictive modeling to high-volume data from various sources.
• Support junior staff and share cross-functional knowledge.
• Collaborate with product teams to implement new ML solutions.

Skills

Python

R

SQL

ML techniques

Distributed computing

Pyspark

Azure/AWS ML Services

Data manipulation

Education

Bachelor’s degree in Mathematics, Statistics, Computer Science, Data Science

Master’s/Ph.D. preferred

Actuarial experience/certification preferred

Tools

Pandas

scikit-learn

NumPy

XGBoost

PyTorch

rpart

caret

Job description

Are you passionate about using data science to drive smarter risk decisions and create meaningful business impact?

Do you enjoy solving complex analytical challenges, working with large-scale data, and helping teams deliver innovative solutions in a collaborative environment?

Aboutthe Business

LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within Insurance, we provide customers with solutions and decision tools that combine public andindustry specificcontent with advanced technology and analytics toassistthem in evaluating and predicting risk and enhancing operational efficiency. Our insurance risk solutions help drive better data-driven decisions across the insurance policy lifecycle-all while reducing risk. You can learn more about LexisNexis Risk at the link below.

https://risk.lexisnexis.com/insurance

About our Team

We are looking for a Sr. Data Scientist I with strong expertise in statistics/modeling and machine learning to join our diverse team of data scientists on the Auto Insurance Rating Analytics team. This individual will play a key role in new product innovation, model development, generating actionable insights, and working closely with the Vertical and Product teams to design and implement new solutions that are cutting edge and support the insurance market.

About the Role

A Senior Data Scientist I should be able to define the 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. A 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

• 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

• Functional Knowledge: Conceptual and practical expertise in own area required

• Business Expertise: Has knowledge of best practices and how subject matter expertise integrates with others; is aware of the competition and the factors that differentiate the company in the market

• Leadership: Occasionally leads the work of small project teams; provides informal guidance to junior staff

• Problem Solving: Typically resolves problems using existing solutions

• Impact: Works with minimal guidance

• Interpersonal Skills: Explains difficult or sensitive information, models auto insurance risk, particularly in the context of credit-based data sources, generally using GLM techniques

• Supports existing models

• Python experience required

• Cloud experience preferred

• 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

Requirements

• Bachelor’s degree in Mathematics, Statistics, Computer Science, Data Science, or other quantitative discipline (or equivalent years of experience); Master’s/Ph.D. degree preferred. Actuarial experience/certification also preferred.
• 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

Risk benefit statement

Learn more about the LexisNexis Risk team and how we work https://relx.wd3.myworkdayjobs.com/RiskSolutions/page/21c296c982531000b79663f3194b0000

U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates.This job is eligible for an annual incentive bonus.

We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click

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We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120.

We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.

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