Senior Data Scientist/AI Analyst

Vantage Risk Companies

1d•$135,000 - $170,000•Remote

About The Position

At Vantage, the Senior Data Scientist/AI Analyst will play a critical role in developing analytical solutions to support our business partners. We welcome candidates with either a data science background with exposure to AI techniques and tools or an AI analyst background that combines strong data analysis skills with deep expertise in leveraging AI models and toolkits and/or building Agentic systems — a successful candidate could come from either path. Data Scientists will leverage advanced statistical, modeling, and AI skills; AI Analysts will leverage strong data/business acumen, creative problem solving, and knowledge of AI and Agentic toolkits. In both cases, the individual will use their respective skillset to help our underwriting, actuarial, and operations partners better understand, quantify, and manage their risks differently, ultimately delivering high-quality, transparent, and business-aligned outcomes. We are seeking a curious, creative, and self-motivated individual who is energized by using data and analytical techniques to solve challenging real-world problems. Vantage’s US colleagues have the flexibility to work anywhere in the United States (excluding US territories and possessions). The base salary expectation for this role is between $135,000 and $170,000. Actual base salary for the selected candidate may be higher commensurate with candidate experience and expectations. Additionally, Vantage offers its colleagues performance-based bonus potential, strong health & welfare benefits, retirement plans with company match, competitive time off plans, a highly flexible work environment, and much more.

Requirements

Bachelor’s degree in a relevant field required; Master’s or Ph.D. in a STEM field is a plus but not required or equivalent professional experience.
5+ years of experience in a Data Science, Applied AI, or Applied R&D role.
Hands-on experience building solutions with large language models; experience fine tuning or developing agentic systems a plus.
Strong foundation in statistics, classical machine learning, and experimentation.
Strong knowledge of Python and/or R; strong knowledge of SQL.
Ability to partner with engineers to operationalize assets in production.
Ability to build analytical and AI-powered web applications via e.g. Streamlit, R Shiny, and/or PowerBI, etc.
Insurance or financial services experience strongly preferred; however, we are open to strong generalists from other domains who can ramp on the industry.
Ability to prioritize and balance speed of development with quality of work.
Experience building end-to-end solutions.
Ability to collaborate with fellow members of the Data, Analytics and Technology group and with our business partners.
Strong project management skills, with emphasis on attention to details and meeting proposed timelines.
Clear, concise communication skills with the ability to share complex information in a way that everyone can understand.
Ability to build productive working relationships with stakeholders.
Ability to process and adapt to change in a rapid growth company environment. Vantage associates are expected to be curious, thrifty, and resourceful to manage through the unknowns of growing a specialty (re)insurance business from the ground up.

Nice To Haves

Hands-on experience with version control systems such as git is a plus but not required.

Responsibilities

Build sustainable solutions for our customers using data analysis, machine learning, and generative AI techniques.
Perform cost-benefit analyses to determine the value of a project and assist in estimating the return on investment of deployed analytical and AI solutions.
Identify new data sources—internal and external, structured and unstructured—and quantify their potential value as inputs to AI, ML, and analytical products.
Partner with data engineers to build analytical and model training datasets and with ML ops engineers to operationalize solutions.
Present solution results to the Data, Analytics, and Technology team, as well as business partners across the organization; translate technical work into business outcomes.
Monitor and maintain solutions once deployed; identify opportunities to increase the impact of deployed solutions.
Perform ad-hoc analyses as needed.
Remain current on industry trends, tools, and techniques.
Be a thought partner. Assist in driving or supporting the business problem solving process.