Data Scientist

Jobtailor; Charlotte (NC); On-site; USD 110,000 - 165,000; Full time

Job summary

Jobtailor in Charlotte, NC is seeking a data analytics professional to build pricing models for Personal Auto and Home lines. You will transform large data sets into actionable insights using predictive modeling and ML, and develop GLMs and gradient boosted trees within MLOps frameworks.

You will collaborate with data engineering, performance analytics, and product teams, using agile methods to deliver analytics support for Personal Lines.

Qualifications

• Master's degree or commensurate work experience in a quantitative field is required.
• At least 2 years of insurance experience, preferably in loss cost modeling or personal lines.
• Proficiency in Python, SQL or R.
• Experience with Linux and bash is preferred.
• Familiarity with Jupyter, VS Code, and RStudio.
• Familiarity with Git and GitHub.
• Familiarity with conda and Docker.
• Familiarity with Spark and Snowflake.
• Familiarity with Quarto and R Markdown.
• Familiarity with AWS (EC2, SageMaker).
• Authorized to work in the US without sponsorship; STEM OPT endorsement not offered.

Responsibilities

• Create analytical solutions to enhance pricing sophistication and competitive advantage for Personal Auto and Home lines.
• Transform large data sets into actionable business insights using predictive modeling and ML.
• Develop GLMs, gradient boosted trees, and MLOps frameworks.
• Collaborate with data engineering, analysis, BI, and data science peers.
• Use agile methodologies to deliver analytics support and modeling solutions to Personal Lines Product Management.
• Engage with peers and business partners across Data Science, Data Engineering, Performance Analytics, Pricing, and Product Management.
• Conduct modeling experiments with senior team members.
• Deliver insights to business partners based on class plan modeling experiments.
• Influence work execution, stakeholder engagement, and project approaches.
• Contribute to larger, strategic engagements with business partners and peers.

Skills

Predictive Modeling

Machine Learning

Generalized Linear Models

Gradient Boosted Trees

MLOps Frameworks

Data Transformation

Statistical Analysis

Data Visualization

Collaboration

Stakeholder Engagement

Influencing Skills

Education

Master's degree in Statistics, Mathematics, Economics, Engineering, Physics, Actuarial Science, or similar analytical field

Tools

Linux

Bash

Git

GitHub

Conda

Docker

Spark

Snowflake

Quarto

R Markdown

Job description

• Create analytical solutions to enhance pricing sophistication and competitive advantage for Personal Auto and Home lines of business
• Transform large data sets into actionable business insights using predictive modeling and machine learning
• Develop and apply generalized linear models, gradient boosted trees, and MLOps frameworks
• Collaborate with data engineering, performance analytics, business intelligence, and data scientist peers
• Use agile methodologies to deliver analytics support and modeling solutions to Personal Lines Product Management
• Meet peers and business partners across Data Science, Data Engineering, Performance Analytics, Pricing, and Product Management
• Perform modeling experiments with more experienced team members
• Deliver insights to business partners based on class plan modeling experiments
• Influence work execution, stakeholder engagement, and project approaches
• Contribute to projects of escalating size and scope
• Tackle larger, more strategic engagements with business partners and peers

Requirements

• Master's degree in Statistics, Mathematics, Economics, Engineering, Physics, Actuarial Science, or similar analytical field; or commensurate work experience with a Bachelor's degree and interest in further education
• At least 2 years of relevant experience in the insurance industry, preferably in loss cost modeling or personal lines products
• Proficiency in Python, SQL or R
• Experience or ability to work with Linux and bash
• Familiarity with Jupyter, VS Code, and RStudio
• Familiarity with Git and GitHub
• Familiarity with conda and Docker
• Familiarity with Spark and/or Snowflake
• Familiarity with Quarto and R Markdown
• Familiarity with AWS, including EC2 and SageMaker
• Candidate must be authorized to work in the US without company sponsorship
• The company will not support the STEM OPT I-983 Training Plan endorsement for this position

Core Competencies

Demonstrates expertise in analytical solution development for pricing strategies in the insurance industry, utilizing advanced modeling techniques and machine learning. Proficient in transforming large data sets into actionable insights while collaborating effectively with cross-functional teams.

Highest-signal resume keywords

• Master's Degree In Statistics, Mathematics, Economics, Engineering, Physics, Actuarial Science
• Proficiency In Python, SQL, Or R
• Experience In Loss Cost Modeling
• Familiarity With AWS, Including EC2 And SageMaker
• Familiarity With Jupyter, VS Code, And RStudio

Hard Skills

• Predictive Modeling
• Machine Learning
• Generalized Linear Models
• Gradient Boosted Trees
• MLOps Frameworks
• Data Transformation
• Statistical Analysis
• Data Visualization

Soft Skills

• Collaboration
• Stakeholder Engagement
• Influencing Skills

Industry Keywords

• Insurance Industry
• Personal Lines Products
• Loss Cost Modeling
• Agile Methodologies

Tools & Technologies

• Linux
• Bash
• Git
• GitHub
• Conda
• Docker
• Spark
• Snowflake
• Quarto
• R Markdown