Senior Data Scientist — Insurance Risk Analytics

LexisNexis Risk Solutions Inc. Company; Alpharetta (GA); On-site; USD 95,000 - 159,000; Full time

Job summary

LexisNexis Risk Solutions is seeking a Senior Data Scientist I to lead and execute data science projects on the Auto Insurance Rating Analytics team. You will develop models, generate actionable insights, and collaborate with cross-functional teams to deliver innovative risk solutions.

Qualifications include a quantitative degree, 3+ years of data manipulation and ML experience, and strong Python/R skills. Cloud experience is preferred and strong communication is essential.

Qualifications

• Bachelor’s degree or higher in a quantitative field.
• 3+ years experience with data manipulation and AI/ML methods.
• Strong programming in Python and/or R with ML libraries.

Responsibilities

• Develop, analyze, and model data to quantify competitive performance.
• Analyze data to propose solutions and new strategies; model impact of changes.
• Apply statistical and ML techniques to manage large high-volume data from multiple sources.
• Lead small project teams occasionally; mentor junior staff.
• Explain complex results clearly; work with GLM methods for risk assessment.

Skills

Statistical modeling

Data manipulation

Machine learning

Self-starting

Education

Bachelor’s degree in Mathematics, Statistics, Computer Science, Data Science, or related field

Master’s/Ph.D. degree preferred

Tools

Python

R

SQL

Pandas

scikit-learn

NumPy

XGBoost

PyTorch

Pyspark

Azure/AWS ML Services

Scala

Job description

LexisNexis Risk Solutions is seeking a Senior Data Scientist I to lead and execute data science projects on the Auto Insurance Rating Analytics team. You will develop models, generate actionable insights, and collaborate with cross-functional teams to deliver innovative risk solutions.

Qualifications include a quantitative degree, 3+ years of data manipulation and ML experience, and strong Python/R skills. Cloud experience is preferred and strong communication is essential.