Research Operations Analyst

Verisk•Boston, MA

About The Position

As a Research Operations Analyst, you will help safeguard the quality, integrity, and efficiency of research and model development across CRS (Catastrophe and Risk Solutions). Reporting to the Head of Research Operations within the Research Department, you will partner with researchers and engineers as a compliance liaison throughout the development lifecycle, conduct model audits ahead of release, and support a broad portfolio of Research Operations initiatives, from training and GenAI enablement to data acquisition and resource planning, all in service of helping Research operate at scale and amplify its impact across the organization. We operate in an environment in perpetual evolution, with access to new compute solutions, new software, and new AI capabilities. Research Operations helps Research maintain its level of excellence by organizing and optimizing the people, processes, tools, and technologies behind our work, ensuring it stays reproducible, well documented, compliant, and efficiently supported. This is a hands-on role for someone with strong attention to detail, solid technical foundations, and a genuine curiosity about how world-class scientific modeling gets done. You will apply and enforce our established procedures while gaining broad exposure to audit, data, AI, and infrastructure topics within a leading modeling organization. You will join a department of more than 100 scientists, engineers, mathematicians, and analysts who develop and maintain a global suite of probabilistic risk models used to quantify and transfer risk worldwide.

Requirements

Bachelor's degree required (Math, Engineering, Science, or related field).
0–3 years of experience; exposure to research, model development, audit, or quality assurance environments is a plus.
Exceptional attention to detail and a methodical, rigorous approach to reviewing work.
Genuine interest in auditing scientific work and understanding how models are built.
Highly organized, able to juggle several initiatives and follow established procedures consistently.
Clear communicator who can raise findings constructively and interact with different roles and levels.
Integrity and independence: able to hold teams to standards respectfully but firmly.
Curious, self-directed learner, energized by an evolving environment of new tools and technologies.
Comfortable operating in an environment of continuous change, flexible and adaptable to shifting priorities.
Working knowledge of Python or a similar scripting language, sufficient to read and assess code.
Experience in project management and software such as Jira.
Familiarity with version control systems (e.g., Git/GitHub).
Strong working skills in Microsoft Office applications, particularly Excel, Word, and PowerPoint.
Hands-on familiarity with generative AI tools and prompt design, with an interest in building reusable AI workflows.
Understanding of reproducibility principles in scientific or data-driven work.

Nice To Haves

Master’s degree preferred.
Familiarity with data management concepts (data catalogs, data lineage) is a plus.
Experience building dashboards or usage reports (e.g., Excel, Power BI) is a plus.

Responsibilities

Conduct methodical audits of models ahead of each release milestone, verifying process and release readiness (including reproducibility of results and validation against benchmarks), data management practices, documentation and team redundancy, compliance requirements, and adherence to code and coding standards.
Advise teams on research compliance, helping protect intellectual property and minimize data footprint.
Implement new processes and requirements for models developed on Nexus, our new platform.
Keep audit procedures and checklists documented and up to date.
Guide teams through Data Usage Requests and advise on terms of use for external data, flagging licensing or usage risks early in development.
Develop training content on research best practices and compliance standards.
Coordinate, and at times lead, training efforts drawing on in-house experts, helping knowledge circulate across the department.
Maintain a curated repository of GenAI prompts and workflows, helping researchers discover, reuse, and extend what works, and tracking emerging use cases to broaden the responsible use of generative AI in Research.
Maintain an overview of data management practices, facilitate the planning of compute, storage, and software needs, and prepare usage overviews that help leadership make informed decisions about resources.
Help coordinate community rituals such as research seminars and team-building events.
Participate in newsletter efforts that showcase the department's work and keep teams connected.