Quantum Algorithm Developer 8

Who Are We?

Taking care of our customers, our communities and each other. That's the Travelers Promise. By honoring this commitment, we have maintained our reputation as one of the best property casualty insurers in the industry for over 170 years. Join us to discover a culture that is rooted in innovation and thrives on collaboration. Imagine loving what you do and where you do it.

Job Category

Technology

Compensation Overview

The annual base salary range provided for this position is a nationwide market range and represents a broad range of salaries for this role across the country. The actual salary for this position will be determined by a number of factors, including the scope, complexity and location of the role; the skills, education, training, credentials and experience of the candidate; and other conditions of employment. As part of our comprehensive compensation and benefits program, employees are also eligible for performance-based cash incentive awards.

Salary Range

$126,500. 00 - $208,700. 00

Target Openings

1

What Is the Opportunity?

At Travelers, we're not just keeping pace with technology - we're leading our industry into the future. Our Emerging Tech team is looking for a Data Engineer (Quantum Algorithm Developer) to help expand the footprint of our foundational research into quantum computing applications for the insurance industry. In this Quantum Algorithm Developer role, you will contribute to the development and evaluation of quantum computing algorithmic solutions with future potential in the insurance industry. You'll also play a critical part in bootstrapping classical-compute solutions that can provide early business value for these problems and serve as precursors to later quantum solutions.

This role is fundamentally a Quantum Algorithm Developer position focused on exploring and implementing quantum computing solutions. This role differs from typical Data Engineer positions in that it emphasizes emerging quantum technology exploration, algorithm development, and research-to-prototype execution over traditional software development. The successful candidate will help bootstrap both classical-compute solutions that provide early business value AND quantum algorithmic solutions that position us for future quantum advantage.

Your work will range from curating insurance-relevant problems at the start, through algorithm development and prototyping, to estimating the potential benefit of future scaled-up versions based on small-scale experimental evidence. You'll collaborate with external partners from industry and academia as we explore one of the most promising frontiers in computing.

What Will You Do?

The primary goal for the first year is to explore and identify promising use cases where quantum computing could provide value in the insurance domain.

Problem Curation and Use Case Identification

Curate exemplary problems with relevancy to the insurance space and potential for quantum advantage

Collaborate with business stakeholders to understand pain points in risk assessment, optimization, and decision-making

Evaluate problems for quantum advantage potential vs. classical sufficiency

Build a portfolio of insurance use cases ranked by quantum readiness and business value potential

Algorithm Development and Prototyping

Apply, adapt, and derive quantum algorithms to solve curated insurance problems

Develop classical-compute reference solutions to establish baselines and provide early business value

Implement quantum algorithm prototypes using Qiskit and other frameworks

Design hybrid quantum-classical approaches that leverage strengths of both paradigms

Performance Analysis and Validation

Analyze algorithm performance through simulations on classical hardware

Conduct experiments on diverse quantum hardware (simulators and actual quantum computers)

Distill scaling properties of algorithm candidates

Estimate potential benefit of future scaled-up versions based on small-scale experimental evidence

Demonstrate value through clear data visualization, plots, and verifiable evidence

Research and Collaboration

Identify, research, and realize key advances in relevant areas of quantum computing

Collaborate within the Applied Research team and with external partners from industry and academia

Review results and justify selected algorithmic solutions with technical rigor

Stay current with quantum computing research and emerging techniques

Contribute to Travelers' quantum computing knowledge base and technical documentation

What Will Our Ideal Candidate Have?

Preferred Qualifications

Hands-On Quantum Implementation

Demonstrated ability to implement and prototype quantum algorithms, not just theoretical understanding

Experience with IBM Qiskit for quantum circuit design and execution

Portfolio showing proof-of-concept quantum implementations - GitHub repositories with quantum code strongly preferred

Ability to translate quantum computing research papers into working code

Experience conducting experiments on quantum hardware simulators and/or actual quantum computers

Quantum Algorithm Knowledge

Fundamental understanding of quantum mechanics principles relevant to quantum computing

Working knowledge of quantum algorithms including:

• QAOA (Quantum Approximate Optimization Algorithm)

• QAE (Quantum Amplitude Estimation)

• QUBO (Quadratic Unconstrained Binary Optimization) formulations

• VQE (Variational Quantum Eigensolver)

Understanding of quantum advantage, quantum supremacy concepts, and scaling properties

Familiarity with quantum error mitigation techniques and current hardware limitations

Research-to-Prototype Execution

Proven ability to conduct proper research and translate findings into working prototypes

Experience moving from academic/theoretical concepts to functional code

Track record of prototyping ideas from research papers or novel approaches

Ability to curate problems with relevancy to specific domains and evaluate them for quantum advantage potential

Skill in distilling scaling properties of algorithm candidates

Classical Computing Reference Solutions (70% of work)

Strong programming skills in Python for prototyping and experimentation (required)

Experience developing classical-compute solutions that provide business value

Ability to implement reference solutions using traditional approaches before quantum implementation

Understanding of when classical approaches are sufficient vs. when quantum may provide advantage

Rigorous Data Analysis and Validation

Strong foundation in applying proper data analysis techniques

Ability to demonstrate value through facts, plots, and verifiable evidence

Experience analyzing algorithm performance through simulations and experiments

Skill in communicating technical findings with visual and statistical rigor

Comfortable with both Bayesian and/or Frequentist statistical frameworks

Advanced Analytics and Optimization

Strong background in optimiz.