Sr. Data Architect

Motion Recruitment; Alpharetta (GA); On-site; USD 130,000 - 150,000; Full time

Job summary

Motion Recruitment is seeking a Senior Data Scientist I with a strong actuarial background to join their Insurance Analytics team. The role focuses on applying statistical modeling and data science to real-world insurance problems beyond traditional rate-making.

You will develop predictive risk models to improve underwriting, segmentation, pricing, and decision-making, leveraging actuarial modeling, GLMs, statistics, and Python within insurance workflows.

Qualifications

• Bachelor's or higher with actuarial background and data science exposure.
• Experience applying actuarial concepts to insurance risk, underwriting, or segmentation.
• Strong programming and analytical capabilities for modeling and data handling.

Responsibilities

• Develop predictive risk models for underwriting, segmentation, and pricing.

Skills

Python

GLMs

Statistical modeling

Data analysis

Actuarial concepts

Machine learning

insurance analytics

Education

Bachelor's degree (4+ yrs)

Master's degree (2+ yrs)

PhD in a relevant field

Tools

R

SQL

Job description

Our client is seeking a Senior Data Scientist I with a strong actuarial background to join their Insurance Analytics team. This role is ideal for an actuarial professional who enjoys applying statistical modeling and data science to real-world insurance problems beyond traditional rate-making.

The Senior Data Scientist will develop predictive risk models and analytical attributes that help insurers improve underwriting, risk segmentation, pricing, and decision-making. The ideal candidate will have hands-on experience with actuarial modeling, GLMs, statistical analysis, and Python, along with an understanding of how predictive models are incorporated into insurance workflows.

APay: 130k - 150k

Key Responsibiliti

• esDevelop predictive risk models and attributes used in underwriting, segmentation, and insurance decisionin
• g.Apply actuarial principles and statistical modeling techniques to evaluate risk and improve model performanc
• e.Build and support models such as GLMs and tree-based methods for insurance application
• s.Design models that can be integrated into carrier underwriting processes and downstream pricing framework
• s.Analyze and manage large, complex datasets from multiple source
• s.Prepare, clean, transform, and validate data for statistical modeling and analysi
• s.Apply data quality, testing, and model performance monitoring best practice
• s.Translate complex analytical findings into clear, actionable insights for Product, Business, and other stakeholder
• s.Partner with Product and Vertical teams to solve insurance-specific problems related to risk evaluation and segmentatio
• n.Support model development, maintenance, enhancement, and production implementatio
• n.Contribute independently to project workstreams while collaborating on larger, complex initiative
• s.Communicate project progress, analytical insights, and outcomes effectivel
• y.Stay current with data science, actuarial, statistical, and insurance industry trends and technologies

s.Required Qualificatio

• nsBachelor's degree in a relevant field with 4+ years of relevant experience,
• ORMaster's degree in a relevant field with 2+ years of relevant experience,
• ORPhD in a relevant fiel
• d.Strong actuarial foundation with experience applying actuarial concepts to insurance risk, underwriting, or segmentatio
• n.Strong proficiency in Python for statistical modeling and data analysi
• s.Experience developing or supporting risk segmentation models, including GLMs, within an insurance environmen
• t.Experience with insurance data, risk modeling, or underwriting-related problem
• s.Experience translating actuarial/statistical models into production-ready analytical solution
• s.Strong understanding of statistical and mathematical modeling, including model assumptions, diagnostics, interpretability, linear/nonlinear models, and machine learning technique
• s.Ability to independently prepare, clean, transform, and analyze large, complex dataset
• s.Strong analytical, problem-solving, and communication skill
• s.Ability to independently own project components, manage priorities, and meet deadline

s.Preferred Qualificatio

• nsProgress toward ASA or equivalent actuarial credentials strongly preferre
• d.Experience with R, SQL, and/or EC
• L.Experience working with Department of Insurance filing
• s.Experience with insurance pricing and underwriting workflow
• s.Familiarity with regulatory requirements and model governanc
• e.Experience with additional machine learning techniques and predictive modelin
• g.Ability to learn new technologies quickly and share knowledge across cross-functional team