Data Scientist I (DSAP)

Renishaw; Alpharetta (GA); Hybrid; USD 59,000 - 99,000; Full time

Benefits offered by this job

Health benefits

401(k) match

Employee share purchase plan

Wellbeing program

Disability & life insurance

Family benefits

Paid time off & volunteering

Job summary

LexisNexis Risk Solutions in Alpharetta, GA is seeking a motivated data scientist to join the Data Science Accelerator Program (DSAP). The two-year program rotates through analytical product development assignments, giving broad exposure to the Insurance Analytics team.

You'll assemble and clean large datasets, apply statistical and machine learning techniques, and document results while collaborating with cross-functional teams.

Qualifications

• Bachelor’s degree in data science/analytics, Computer Science, Mathematics, or related fields (Engineering, Economics, Business).
• Coursework or project experience in Python or R; familiarity with SQL is a plus.
• Interest in data analysis, predictive modeling, and machine learning.

Responsibilities

• Assist with assembling, cleaning, and organizing large datasets for analysis.
• Support data merging and parsing to uncover trends and patterns.
• Apply statistical and machine learning techniques under guidance of senior data scientists.
• Document model code, track results, and validate predictive models.

Skills

Python

R

SQL

Data visualization

Education

Bachelor's degree in data science/analytics/CS/Math

Tools

Tableau

Power BI

Matplotlib

Seaborn

Job description

About the 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 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 Insurance Analytics team are the trusted leaders in analytics excellence, delivering innovative, data-driven solutions through cutting-edge data science and strategic risk solutions to drive market leadership, impactful change, and lasting value for our customers and stakeholders. The team is responsible for new product innovation, model development, and creating actionable insights for our customers. We work closely with the Vertical and Product teams to design and implement new solutions for the insurance and OEM markets. By harnessing the power of data, our analytics team empowers insurers to make informed decisions, optimize risk segmentation, and enhance underwriting strategies, ultimately driving success in an ever-evolving insurance landscape.

About the Role

We are seeking a highly motivated data scientist to join the Data Science Accelerator Program (DSAP) that provides broad learning opportunities across the Data Science organization within 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. 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 data scientists.
• 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/analytics, Computer Science, Mathematics, or other degrees in fields like Engineering, Economics, and Business.
• 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.

U.S. National Base Pay Range: $59,200 - $98,600. Geographic differentials may apply in some locations to better reflect local market rates.This job is eligible for an annual incentive bonus.

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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