Senior Insurance Data Science Consultant

ERNIE'S AUCTION CTR
Boston, United States of America
9 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior
Compensation
$ 204K

Job location

Boston, United States of America

Tech stack

Data analysis
Python
Machine Learning

Job description

This role is based in Texas, supporting our regional clients, and is part of our North America team headquartered in Boston, MA. What you'll do

  • Lead pricing strategy discussions using advanced analytics and actuarial insight, ensuring decisions are grounded in data and aligned to business outcomes.
  • Engage directly with senior executives, translating complex technical results into clear, compelling narratives that drive alignment and action.
  • Build and evolve predictive models that assess risk and forecast demand-directly shaping pricing and business decisions across insurance products.
  • Influence decision-making at the highest levels by connecting analytics to business value and strategic priorities.
  • Demonstrate Earnix capabilities in executive and client settings, showing not just how the platform works-but what it enables.
  • Lead onboarding and training for new users, ensuring fast adoption and rapid time-to-value from day one.
  • Act as a trusted advisor to clients, bridging business, analytics, and technology to deliver measurable impact.

Requirements

We are seeking a highly experienced and strategically-minded Senior Insurance Data Science Consultant to join our growing analytics team. This role is ideal for a seasoned professional with actuarial experience and deep expertise in predictive modeling, machine learning, and insurance analytics. You will play a pivotal role in influencing client decision-making, shaping pricing strategies and delivering actionable insights to clients across multiple lines of business., * 15+ years of experience in the insurance industry, with deep expertise in analytics, actuarial modeling, and predictive techniques.

  • Strong hands-on experience with machine learning and statistical modeling to improve the accuracy, performance, and business impact of risk and pricing models.
  • Advanced proficiency in programming languages such as Python and R, applied to building, validating, and deploying scalable analytical solutions.
  • Experience working with intelligent decisioning platforms (such as Earnix or similar), integrating models into real-time pricing and personalization workflows.
  • Strong executive presence with the ability to engage, influence, and advise senior stakeholders in client organizations.
  • Willingness and flexibility to travel up to 40% domestically and internationally.

You'll excel by: Communicating with clarity and executive presence, making complex data and models actionable for senior leadership. Building trusted client relationships, understanding business needs, and delivering insights that drive measurable strategic outcomes. Collaborating across teams, sharing knowledge and mentoring others to elevate the organization's analytical capability. Adapting quickly to new challenges, staying curious and proactive in a fast-paced, innovation-driven environment. Salary Range: $ 180,000-204,000 per year

About the company

Earnix is the premier provider of mission-critical, cloud-based intelligent decisioning across pricing, rating, underwriting, and product personalization. These fully-integrated solutions provide ultra-fast ROI and are designed to transform how global insurers and banks are run by unlocking value across all facets of the business. Earnix has been innovating for insurers and banks since 2001 with customers in over 35 countries across six continents and offices in the Americas, Europe, Asia Pacific, and Israel, Company Description At EVERSANA, we are proud to be certified as a Great Place to Work across the globe. We're fueled by our vision to create a healthier world. How? Our global t…, © 2026 Careerjet All rights reserved

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