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Actuarial Scientist Jobs in Georgia (NOW HIRING)

Would you like to apply advanced actuarial science and machine learning to build predictive models that directly influence underwriting, pricing, and risk decisions for insurers at scale? About the ...

Minimum of Bachelor's degree in risk management, finance, economics, actuarial science, mathematics, statistics, or related field * Programming skills in SQL/R/python * Must be authorized to work in ...

Bachelor's degree in Actuarial Science, Economics, Mathematics, Statistics, or a related field. * Experience in pricing, valuation, and/or capital modeling. * Strong proficiency in Microsoft Office ...

... in actuarial science, applied statistics, financial analysis, insurance, and mathematics. • Demonstrate consistent progress towards achieving certification as an Associate of the Society of ...

Strong academic background in actuarial science, applied statistics, financial analysis, insurance, and mathematics * Ability to work on multiple projects and prioritize work without intensive ...

Strong academic background in actuarial science, applied statistics, financial analysis, insurance, and mathematics * Ability to work on multiple projects and prioritize work without intensive ...

Bachelor's degree in Actuarial Science, Math, a related field, or equivalent years of industry experience. Aon is not accepting unsolicited resumes from search firms for this position. If you are a ...

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Actuarial Scientist information

See Georgia salary details

$43.1K

$96K

$133.4K

How much do actuarial scientist jobs pay per year?

As of May 28, 2026, the average yearly pay for actuarial scientist in Georgia is $95,988.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,200.00 and $107,200.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Actuarial Scientist, and why are they important?

To thrive as an Actuarial Scientist, you need strong mathematical and statistical skills, analytical thinking, and typically a bachelor's degree in actuarial science, mathematics, or a related field, along with progress toward professional actuarial certifications (such as SOA or CAS exams). Familiarity with statistical analysis software, spreadsheets, and actuarial modeling tools is essential. Exceptional problem-solving, communication, and attention to detail are standout soft skills for this role. These skills and qualifications enable actuaries to accurately assess risk, inform business decisions, and ensure financial stability for organizations.

How do Actuarial Scientists typically collaborate with other departments within an organization?

Actuarial Scientists frequently work closely with departments such as finance, underwriting, IT, and product development to assess risk and develop strategies. Collaboration often involves sharing and interpreting complex data, contributing to cross-functional teams, and supporting decision-making processes with quantitative analysis. Regular meetings and joint projects are common, allowing Actuarial Scientists to provide insights that guide pricing, risk management, and business planning. This collaborative environment fosters broader business understanding and can open pathways to leadership or specialized roles within the organization.

What are actuarial scientists?

Actuarial scientists, also known as actuaries, are professionals who use mathematics, statistics, and financial theory to assess risk and uncertainty in various industries, most commonly in insurance, pensions, and finance. They analyze data to estimate the likelihood of future events and help organizations develop policies that minimize the cost of risk. Actuaries play a crucial role in designing insurance policies, pension plans, and other financial strategies by predicting financial outcomes and ensuring long-term stability.

What is the difference between Actuarial Scientist vs Actuary?

AspectActuarial ScientistActuary
CredentialsTypically requires a bachelor's degree in mathematics, statistics, or related field; professional actuarial exams are often pursuedRequires passing multiple professional actuarial exams and obtaining certification (e.g., ASA, FSA)
Work EnvironmentResearch-focused, data analysis, model development in insurance, finance, or consulting firmsRisk assessment, pricing, and reserving in insurance companies, consulting firms, or government agencies
Industry UsageCommonly used in insurance, finance, and risk management sectorsPrimarily in insurance, pension plans, and risk management industries

While both roles involve statistical analysis and risk modeling, Actuarial Scientists often focus on research and model development, whereas Actuaries apply these models to assess risk, set premiums, and ensure financial stability in insurance and related industries.

What cities in Georgia are hiring for Actuarial Scientist jobs? Cities in Georgia with the most Actuarial Scientist job openings:
Infographic showing various Actuarial Scientist job openings in Georgia as of May 2026, with employment types broken down into 3% As Needed, 91% Full Time, 3% Part Time, 1% Temporary, 1% Contract, and 1% Nights. Highlights an 57% Physical, 11% Hybrid, and 32% Remote job distribution, with an average salary of $95,988 per year, or $46.1 per hour.
Sr Data Scientist I (Hybrid)

Sr Data Scientist I (Hybrid)

RELX

Alpharetta, GA

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 7 days ago


Job description

Would you like to apply advanced actuarial science and machine learning to build predictive models that directly influence underwriting, pricing, and risk decisions for insurers at scale?

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 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

The Insurance Analytics team are the trusted leaders in analytics excellence, delivering innovative, data-driven solutions throughcutting-edgedata science and strategic risk solutions to drive market leadership, impactful change, and lasting value for our customers and stakeholders.The teamis responsible fornew product innovation, model development, and creating actionable insights for our customers. We work closely with the Vertical and Product teams to design and implementnew solutionsforthe insuranceand OEMmarkets. By harnessing the power of data, our analytics team empowers insurers to make informed decisions,optimizerisk segmentation, and enhance underwriting strategies,ultimately drivingsuccess in an ever-evolving insurance landscape.

About the Role

We are seeking a Senior Data Scientist I to join our Insurance Analytics team, with a strong foundation in actuarial science, statistical modeling, and data science. In this role, you will contribute to the development of innovative insurance products, advanced predictive models, and data-driven insights that inform key business decisions.

You will partner closely with Product and Vertical teams to design and deliver analytical solutions that address complex insurance challenges and support evolving market needs. This role is ideal for someone who combines deep actuarial expertise with strong modeling intuition, is comfortable working with complex datasets, and can effectively translate analytical findings into clear, actionable recommendations that drive business and product outcomes.

Responsibilities:

  • Developing and enhancing statistical and machine learning models using structured and unstructured data to generate predictive insights and attributes.
  • Design and building data pipelines and analytical solutions that support risk segmentation and insurance use cases.
  • Providing actuarial expertise and recommendations to inform model development, risk segmentation, and support rate filings.
  • Researching and applying innovative data science methodologies to solve complex business problems.
  • Managing and analyzing large, complex datasets, including data storage, processing, and quality assurance.
  • Applying best practices for data validation, testing, and model performance monitoring.
  • Collaborating with team members to share knowledge, strengthen capabilities, and contribute to a strong analytical culture.
  • Identifying and leveraging new data sources to improve and validate existing models.
  • Partnering with internal stakeholders to understand business needs, troubleshoot challenges, and deliver actionable insights.
  • Maintaining a strong understanding of team tools, technologies, and evolving industry trends.
  • Applying business and domain knowledge to drive effective, practical solutions.
  • Communicating progress, insights, and outcomes clearly to stakeholders.
  • Supporting team excellence by upholding high standards of quality, accountability, and execution.

Requirements:

  • Minimum undergraduate degree in relevant field and 4+ years of relevant work experience
  • Or a master's degree in a relevant field and 2+ years of relevant work experience.
  • Or a PhD in a relevant field.
  • Strong expertise in Python. Coding skills in R, SQL, ECL are a plus.
  • Good foundation in actuarial science, including experience applying actuarial principles to pricing, risk segmentation, or model development.
  • Strong foundation in statistical and mathematical modeling, including model assumptions, diagnostics, and interpretability. This includes linear and non linear models along with ML techniques.
  • Extensive 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 nice to have.

Technical/Professional Experience

  • Able to build or test new processes with senior guidance. Domain expert in Data Science, Actuarial Science and/or Statistical Analysis to build advanced models and roll into production.
  • Scopes and execute analytical approaches for moderately complex problems, seeking input where needed.
  • Supports, maintains, and enhances existing models (e.g., GLM and tree-based methods).
  • Applies statistical, mathematical, predictive modeling and analytical techniques to work with large, complex datasets from diverse sources.

Data Skills

  • Independently prepares, cleans, and transforms data for analysis and modeling.
  • Applies a range of data processing techniques and explores new methods to improve data quality and usability.

Project Management Skills

  • Owns and delivers components of projects independently, including planning and execution of key tasks.
  • Contributes to larger, more complex projects by executing defined workstreams and meeting timelines.

Domain/Industry Skills

  • Applies core data science and statistical methods within an insurance context.
  • Strong foundation in actuarial science, including experience applying actuarial principles to pricing, risk segmentation, or model development.
  • Understands and applies machine learning techniques, including hypothesis testing, sampling methods, model development (linear and non-linear), validation, and data pipelines.

Behavioral Competencies

  • Takes initiative and ownership of work, proactively addressing challenges and identifying opportunities for improvement.
  • Collaborate effectively with teammates, supporting a positive and accountable team environment.
  • Balances innovation with practical business needs and team priorities
  • Demonstrates accountability, follows through on commitments, and maintains high standards of work.
  • Shows willingness to stretch beyond core responsibilities and support team success.

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, 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
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 here to access benefits specific to your location.

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