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Insurance Statistician Jobs in Washington (NOW HIRING)

GEICO

Senior Insurance Product Analyst II

Bethesda, MD · On-site +1

$71K - $141K/yr

Developing, preparing, and interpreting statistical analyses of insurance sales, claims experience, or other key business metrics to help support strategic decisions within the business unit

Otsuka

Associate Director, Biostatistics

Rockville, MD · On-site +1

Lead statistical input into study design, protocol development, analysis planning, interpretation ... Company provided Basic Life, AD&D, Short-term and Long-term Disability insurance * Tuition ...

Celestar Corporation

Data Scientist- Senior

Washington, DC · On-site

$175K - $180K/yr

For example, we offer Company-Paid Benefits that include Employee and Family Dental Insurance ... Performs statistical analysis, applies data mining techniques, and builds high-quality prediction ...

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Insurance Statistician information

What is an insurance statistician?

An Insurance Statistician analyzes data related to insurance claims, policies, and risk factors to help insurers make informed decisions. They use statistical models and actuarial techniques to assess trends, calculate probabilities, and estimate future risks. Their insights support underwriting, pricing strategies, and risk management. They often work with large datasets, programming languages, and statistical software. This role helps insurance companies remain profitable while offering fair policy rates.

What are the key skills and qualifications needed to thrive as an insurance statistician?

To thrive as an Insurance Statistician, you need a strong background in statistics, mathematics, and actuarial science, typically supported by a relevant bachelor’s or master’s degree. Proficiency with statistical analysis software such as SAS, R, or Python, as well as familiarity with insurance-focused modeling systems, is vital, and professional certifications like ASA or CSPA can be advantageous. Strong analytical thinking, attention to detail, and clear communication skills help distinguish top performers in this field. These qualifications enable Insurance Statisticians to effectively interpret complex data, support business decisions, and comply with industry regulations.

What are the most common challenges faced by insurance statisticians in their day-to-day work?

Insurance Statisticians often face challenges such as working with large and sometimes incomplete datasets, ensuring the accuracy of complex risk models, and keeping up with regulatory changes that affect data reporting. They must work closely with underwriters, actuaries, and other departments to interpret data findings and translate them into actionable business strategies. Continuous learning and adaptability are essential, as industry practices and statistical techniques evolve rapidly. Despite these challenges, the role offers the satisfaction of directly impacting an organization's financial stability and customer offerings.

Are insurance statisticians still in demand?

Insurance statisticians are still in demand due to the ongoing need for risk assessment, data analysis, and actuarial modeling in the insurance industry. Strong skills in statistical software, data management, and certifications such as ASA or FSA can enhance job prospects in this field.

What are popular job titles related to Insurance Statistician jobs in Washington?

For Insurance Statistician jobs in Washington, the most frequently searched job titles are:

What job categories do people searching Insurance Statistician jobs in Washington look for?

The top searched job categories for Insurance Statistician jobs in Washington are:

Insurance Statistician jobs near you
Infographic showing various Insurance Statistician job openings in Washington as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 17% Part Time, 2% Temporary, and 8% Contract. Highlights an 85% Physical, 1% Hybrid, and 14% Remote job distribution.

SAS to Python / R Migration Architect

Ignite IT

Suitland, MD • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 26 days ago

Job description

The SAS to Python/R Migration Architect is responsible for end-to-end strategy, design, and governance of large-scale analytical and statistical code migrations from SAS to modern open-source ecosystems (Python and R). This role focuses on assessment, architecture, standards, risk management, and validation, working closely with stakeholders and development teams to ensure accuracy, performance, and regulatory fidelity.

This is a hands-on technical leadership role, not just documentation or oversight.

Key Responsibilities

  • Lead enterprise-scale migrations from SAS (Base SAS, PROC SQL, STAT, ETS, MACRO, etc.) to Python and/or R
  • Perform detailed SAS estate assessments, including:
    • Code inventory and dependency mapping
    • Macro complexity analysis
    • Data access patterns (SAS datasets, DBs, flat files)
    • Statistical method equivalency analysis
  • Define target-state architecture for Python/R analytics platforms (libraries, frameworks, environments)
  • Establish migration patterns and standards, including:
    • SAS PROC → Python/R library mappings
    • Macro-to-function translation strategies
    • Reusable templates and shared components
  • Design validation and reconciliation frameworks to ensure:
    • Statistical equivalence
    • Numeric tolerances
    • Regulatory and audit compliance
  • Guide performance optimization strategies for large datasets
  • Identify automation opportunities (code scanners, translators, test harnesses)
  • Lead technical reviews and approve migrated code
  • Mentor developers and review complex conversions
  • Communicate migration risks, tradeoffs, and timelines to leadership

Requirements

  • 8+ years of advanced analytics or statistical programming experience
  • 5+ years hands-on SAS development (Base SAS, PROC SQL, MACRO, STAT)
  • Proven experience architecting or leading SAS → Python and/or R migrations
  • Deep expertise in:
    • Python (NumPy, Pandas, SciPy, statsmodels, scikit-learn)
    • and/or R (tidyverse, data.table, caret, survival, forecast)
  • Strong understanding of statistical methods parity between SAS and open-source tools
  • Experience with data platforms (SQL databases, cloud storage, data lakes)
  • Familiarity with CI/CD, version control, and testing frameworks for analytics code
Nice to Have
  • Experience in regulated environments (government, healthcare, finance)
  • Prior work modernizing legacy analytics platforms
  • Exposure to cloud analytics stacks (AWS, Azure, GCP)
  • Experience designing automated validation frameworks

Benefits

  • 401(k)
  • 401(k) matching
  • Dental insurance
  • Flexible spending account
  • Health insurance
  • Life insurance
  • Paid time off
  • Professional development assistance
  • Referral program
  • Tuition reimbursement
  • Vision insurance