Sr. Data Scientist

Vertafore•Denver, CO

6d•Onsite

About The Position

At Vertafore, Data Scientists play a critical role in transforming data into intelligent products and business outcomes. This role combines advanced analytics, machine learning, generative AI, and experimentation to drive innovation across our insurance technology platform. The ideal candidate is a hands-on practitioner who can identify opportunities in complex datasets, develop production-grade machine learning and AI solutions, and collaborate cross-functionally to deliver measurable business impact. This role requires expertise in both traditional machine learning and emerging AI technologies, including large language models (LLMs), retrieval-augmented generation (RAG), agentic workflows, and AI-assisted product development.

Requirements

Bachelor’s degree or equivalent in a quantitative field such as Computer Science, Applied Mathematics, Engineering, or related field
6+ years of experience working with data sets and building statistical models
Strong communication and interpersonal skills
Passion for data and analytics
Ability to quickly learn and execute
Experience with machine learning platforms: Tensorflow, Keras, HuggingFace, Amazon SageMaker/AWS
Experience with machine learning tasks: classification, regression, clustering, dimensionality reduction, natural language processing, recommender systems
Experience with machine learning operations: data management, data monitoring, model development, model deployment, model monitoring
Experience with programming languages and related tools: Python, Git, SQL

Nice To Haves

6+ years of experience working with complex data sets and building statistical models
Master’s Degree in Data Science/Statistics

Responsibilities

Explore, profile, and assess large structured and unstructured datasets.
Identify opportunities for AI, machine learning, automation, and predictive analytics.
Partner with product, engineering, and business stakeholders to translate business challenges into data science and AI solutions.
Source, evaluate, and integrate internal and external data assets.
Design, develop, evaluate, and deploy machine learning models that support customer, operational, and product initiatives.
Build predictive, classification, recommendation, forecasting, and optimization models.
Develop and evaluate generative AI solutions utilizing foundational models and LLMs.
Implement Retrieval-Augmented Generation (RAG), semantic search, vector databases, and agent-based AI systems where appropriate.
Fine-tune, evaluate, and monitor AI models for performance, accuracy, bias, and business value.
Apply modern feature engineering, model selection, hyperparameter optimization, and validation techniques.
Partner with Product Management to identify and prioritize AI-driven product capabilities.
Develop proof-of-concept and prototypes that accelerate innovation.
Evaluate emerging AI technologies and recommend adoption strategies.
Contribute to AI roadmaps and Enterprise AI strategy.
Build and maintain scalable ML and AI pipelines.
Collaborate with software engineers to deploy and monitor production models.
Implement CI/CD practices for machine learning and AI systems.
Establish model monitoring, drift detection, retraining, observability, and governance processes.
Ensure reproducibility, traceability, and auditability of data science assets.
Apply ethical AI principles, fairness assessments, and risk management practices.
Ensure compliance with security, privacy, regulatory, and governance requirements.
Participate in AI governance reviews and model risk assessments.
Mentor data scientists and analysts.
Conduct code reviews, model reviews, and technical design reviews.
Communicate complex technical concepts to technical and non-technical audiences.
Contribute to best practices, standards, and reusable AI frameworks.