About the Business:

LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within our Insurance vertical, we provide customers with solutions and decision tools that combine public and industry specific content with advanced technology and analytics to assist them 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:

The Data Science Accelerator Program provides broad learning opportunities across the Data Science organization of the LexisNexis Insurance Division. Successful candidates will holistically learn our business during this two-year program while rotating through a series of Analytical product development related assignments and projects. Once complete, a permanent team will be assigned to the Data Scientist. Potential assignments include but are not limited to these analytical teams: data wrangling, attribute creation, model development, solution implementation and quality assurance.

About the Role:

Candidates will be exposed to the full lifecycle of an Insurance policy including customer acquisition and retention, point of contact, underwriting, pricing, compliance and claims. Candidates will work with solutions across the Auto, Home, Life and Commercial insurance markets. The role will be Hybrid located at our headquarters in Alpharetta, GA and may include some travel.

Responsibilities:

• Assist with assembling, cleaning, and organizing large datasets to prepare them for analysis.

• Support team members in merging and parsing data to uncover trends and patterns.

• Learn to apply statistical and machine learning techniques under the guidance of senior analysts.

• Help document model code, track results, and contribute to validating predictive models.

• Assist in creating attributes and rules from raw data to support analytic projects.

• Contribute to data visualization efforts to communicate findings.

• Participate in preparing responses to client inquiries regarding data, score calculations, or analytic outputs.

• Document work clearly and practice presenting results in a team setting.

Requirements:

• Hold a bachelor’s in data science, Math, Stats, Comp Sci, or other quantitative/applied math field.

• Coursework or project experience in Python or R; familiarity with SQL is a plus

• Interest in data analysis, predictive modeling, and machine learning.

• Exposure to data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn) is desirable.

• Strong problem-solving skills with a willingness to learn and adapt.

• Ability to communicate ideas clearly and work collaboratively with others.

Working for you:

We know that your wellbeing and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer:

● Health Benefits: Comprehensive, multi-carrier program for medical, dental and vision benefits
● Retirement Benefits: 401(k) with match and an Employee Share Purchase Plan
● Wellbeing: Wellness platform with incentives, Headspace app subscription, Employee Assistance and Time-off Programs
● Short-and-Long Term Disability, Life and Accidental Death Insurance, Critical Illness, and Hospital Indemnity
● Family Benefits, including bonding and family care leaves, adoption and surrogacy benefits
● Health Savings, Health Care, Dependent Care and Commuter Spending Accounts
● In addition to annual Paid Time Off, we offer up to two days of paid leave each to participate in Employee Resource Groups and to volunteer with your charity of choice

Learn more about the LexisNexis Risk team and how we work here.

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.

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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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