Machine Learning Scientist - Remote

Description

Tower Hill Insurance Group has an exciting opportunity for a talented Machine Learning Scientist who enjoys intellectual challenges and is seeking a rewarding career with a company that is experiencing growth. Not only is Tower Hill Insurance one of Florida's most trusted names in homeowners insurance, but it offers great opportunities for career advancement and personal growth, along with very competitive benefits and rewards.

We are growing at a consistent pace and seek professional individuals with drive, team mentality, who want to make an impact, and are committed to a long-term career in the insurance industry.

The Machine Learning (ML) Scientist develops actionable insights and recommendations in support of business objectives using in‑house and external data sources. This position utilizes problem‑solving skills to collaborate with business and data engineering professionals for timely and reliable delivery of data solutions. This role leverages the team’s deep expertise in data engineering, data science, advanced analytics, and insurance industry data to aid business partners in risk management, drive efficiencies, and improve customer experience.

• Partner with business stakeholders to scope, structure, and drive analytical projects from requirements through delivery. Present findings and recommendations clearly to both technical and non‑technical audiences.
• Source, validate, and integrate structured and unstructured data across platforms. Conduct exploratory data analysis to reveal data quality issues and identify opportunities.
• Analyze business trends, time series patterns, model performance, and causal relationships using advanced statistical and machine learning / deep learning methods to inform strategic decisions.
• Design, build, and deploy machine learning / deep learning models — including NLP, computer vision, and LLM‑based solutions — from rapid prototyping through production deployment.
• Create visualizations, dashboards, and reports that communicate analytical and model results to support decision‑making across the organization.
• Own and maintain recurring analytical, reporting, and model‑monitoring processes.
• Document data pipelines, model architecture, analytical frameworks, and deliverables for knowledge sharing across technical and non‑technical teams.

This job description reflects the general duties considered necessary to describe the essential functions of the job and should not be considered a complete description of all the work requirements and expectations of the position. Tower Hill reserves the right to assign duties not listed herein as necessary to accomplish the goals of the organization.

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

High School Diploma or GED required. Bachelor’s Degree in Computer Science, Statistics, Mathematics, Engineering, or related field required. Master’s Degree or higher preferred.

Minimum of five (5) years of relevant work experience in machine learning and/or deep learning required, including the following:

• Advanced Proficiency in Python.
• Demonstrated ability to build and deploy ML models using frameworks such as scikit‑learn, PyTorch, Hugging Face Transformers.
• Experience working with cloud data platforms and warehouses (e.g., Snowflake, Postgre
  
  SQL) and cloud storage (e.g., S3).Strong written and verbal communication skills with the ability to present complex technical concepts and insights to non‑technical stakeholders.
• Proven ability to work independently, drive projects forward with minimal oversight, and execute in stakeholder‑facing environments.

The following work experience is highly preferred:

• Experience with deep learning, NLP, computer vision, or large language model development and deployment.
• Hands‑on experience with statistical methods (hypothesis testing, regression,…