Senior Data Scientist

About the company

Gradient AI is the decision-intelligence partner for the insurance industry, giving customers an advantage in how they make decisions by revealing risk others miss and translating it into stronger performance and real-world impact. Our platform harnesses a vast industry data lake – tens of millions of policies and claims enriched with economic, health, geographic, and demographic signals – integrating cleanly with existing workflows to make complex risk clear, usable, and actionable. Our customers include carriers, brokers, consultants, and specialized insurance organizations across the industry. We are backed by $56M in Series C funding and scaling fast.

This is a fully remote opportunity with hybrid available to those local to Boston.

About the role

We are looking for a Senior Data Scientist to advance our core AI models and drive them to market in collaboration with data science, product, and engineering partners. In this role, you will own well-scoped models end-to-end – working independently to ship measurable uplift on the AI capabilities at the heart of our products.

Responsibilities

• Leverage the best of modern deep learning & large language models with traditional data science techniques to create powerful hybrid models with real uplift.
• Brainstorm, prototype, prove, deploy, and realize the value of your work in market quickly.
• Tell stories with your data. Inspire trust in customers, stakeholders, and prospects by turning murky math into a powerful message that drives the bottom line.

Qualifications

• Bachelor's degree in Computer Science, Data Science, Biostatistics, Mathematics, or similar related field AND 3-5 years of professional data science experience building predictive models
• OR Master's or Ph.D in Computer Science, Data Science, Biostatistics, Mathematics, or similar related field AND 1-2 years of professional data science experience building predictive models
• You like getting things over the line. You have an insatiable desire to deliver value now and improve next.
• You are not a software engineer, but you give them a run for their money. You prefer Python to R and don't understand why there is still a debate.
• You love to take initiative and spearhead new projects, even if they are not well defined. You build systems bigger than you.
• You contribute to open source, build packages your peers want to use, or design frameworks to elevate your team. Reuse is a strategy, not a buzzword.

Skills

• Hands-on comprehensive experience with deep learning frameworks such as PyTorch or TensorFlow, and an understanding of modern AI architectures (e.g., Transformers, Neural Networks, LLMs).
• Advanced proficiency in Python and its core data science ecosystem (e.g., Pandas, NumPy, Scikit-learn, LightGBM, etc.)
• Strong technical communication and collaboration skills within agile squads and DS leadership
• Familiarity with SQL, Relational databases, and cloud environments like AWS/Azure/Google/Databricks
• MLOps and hands-on experience taking models from notebook to production — Experiment tracking, packaging, containerization (Docker), model serving and APIs, CI/CD, and pipeline orchestration

Bonus Qualifications

• Fluency with actuarial methods and working with actuaries is a plus
• Familiarity with healthcare and medical data
• Familiarity with underwriting and claims, or predicting long-tailed and/or rare events

Benefits

• Generous stock options – we all get to own a piece of what we're building
• Unlimited vacation days
• Flexible schedule that supports working from home
• Full benefits package includes medical, dental, vision, 401k, paid parental leave, and more
• Ample opportunities to learn and take on new responsibilities

Pay

Salary range: $135,000–$165,000 base salary annually. This role is also eligible for an annual performance bonus, equity grant, and a comprehensive benefits package.

The actual salary offered will depend on the level at which the candidate is hired, as well as their experience, skills, qualifications, and location. Compensation may grow over time through merit-based increases, promotions, and company-wide adjustments.