Senior Data Scientist

<p><strong><em>This is a fully remote opportunity with hybrid available to those local to Boston.</em></strong></p>

<p><strong>Gradient AI:&nbsp;&nbsp;</strong>&nbsp;&nbsp;</p>

<p>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.&nbsp;Our platform harnesses a vast industry data lake&nbsp;–&nbsp;tens of millions of policies and claims enriched with economic, health, geographic, and demographic signals&nbsp;–&nbsp;integrating cleanly with existing workflows to make complex risk clear, usable, and actionable.&nbsp;Our customers include carriers, brokers, consultants, and specialized insurance organizations across the industry.&nbsp; We are backed by $56M in Series C funding&nbsp;and&nbsp;scaling fast&nbsp;–&nbsp;and&nbsp;it's&nbsp;an exciting time to join the team!&nbsp;</p>

<p><strong>About the Role:&nbsp;&nbsp;</strong>&nbsp;&nbsp;</p>

<p>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&nbsp;–&nbsp;working independently to ship measurable uplift on the AI capabilities at the heart of our products.&nbsp;</p>

<p><strong>How you will make an impact:</strong>&nbsp;</p>

<ul>

<li>Leverage the best&nbsp;of modern&nbsp;deep learning&nbsp;&amp;&nbsp;large language models&nbsp;with&nbsp;traditional data science techniques&nbsp;to create powerful hybrid models with&nbsp;real uplift.&nbsp;</li>

<li>Brainstorm, prototype,&nbsp;prove,&nbsp;deploy, and realize the value of your work in&nbsp;market&nbsp;quickly.&nbsp;</li>

<li>Everything&nbsp;you would expect&nbsp;on&nbsp;a world-class data science team&nbsp;solving world-class problems.&nbsp;&nbsp;Big data.&nbsp;&nbsp;Federated learning.&nbsp;&nbsp;Unstructured data challenges.&nbsp;&nbsp;Timeseries and sequence&nbsp;modelling.&nbsp;&nbsp;A self-serve buffet of techniques from GLMs&nbsp;to&nbsp;XGBoost&nbsp;to Transformers.&nbsp;</li>

<li>Tell&nbsp;stories with your data.&nbsp;&nbsp;Inspire&nbsp;trust in customers, stakeholders, and prospects&nbsp;by turning murky math into a powerful message that&nbsp;drives the bottom line.&nbsp;</li>

</ul>

<p><strong>Who you are and why we want to work with you:</strong></p>

<ul>

<li>You&nbsp;like getting things over the line.&nbsp;&nbsp;You have an insatiable desire to deliver value now and improve next.&nbsp;&nbsp;MVP perfection is achieved not when&nbsp;there is nothing more to add, but&nbsp;when&nbsp;there is nothing left&nbsp;to take away.&nbsp;</li>

<li>You are not a software engineer, but you give them a run for their money.&nbsp;&nbsp;You prefer&nbsp;Python to&nbsp;R and&nbsp;don’t&nbsp;understand why&nbsp;there is&nbsp;still a debate.&nbsp;&nbsp;Jupyter is&nbsp;a necessary evil, and&nbsp;you’ve&nbsp;never met a command line that scared you away.&nbsp;</li>

<li>You&nbsp;still&nbsp;do a better job than Claude,&nbsp;and&nbsp;you’re&nbsp;skeptical of your friends&nbsp;who&nbsp;say they never code any more.&nbsp;</li>

<li>You love to take initiative&nbsp;and spearhead new projects, even if they are not well defined.&nbsp;</li>

<li>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.&nbsp;&nbsp;Reuse is a strategy, not a buzzword.&nbsp;</li>

</ul>

<p><strong>Skills needed to succeed: </strong>&nbsp;&nbsp;</p>

<ul>

<li>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&nbsp;</li>

<li>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&nbsp;</li>

<li>Hands-on&nbsp;comprehensive&nbsp;experience with deep learning frameworks such as&nbsp;PyTorch&nbsp;or TensorFlow, and an understanding of modern&nbsp;AI&nbsp;architectures (e.g., Transformers, Neural Networks, LLMs). &nbsp;</li>

<li>Advanced&nbsp;proficiency&nbsp;in Python and its core data science ecosystem (e.g., Pandas, NumPy, Scikit-learn,&nbsp;LightGBM, etc.) &nbsp;</li>

<li>Strong technical communication and collaboration skills&nbsp;within&nbsp;agile squads and DS leadership&nbsp;</li>

<li>Familiarity&nbsp;with&nbsp;SQL, Relational databases, and&nbsp;cloud environments like AWS/Azure/Google/Databricks&nbsp;</li>

<li>MLOps&nbsp;and hands-on experience taking models from notebook to production —&nbsp;Experiment tracking,&nbsp;packaging, containerization (Docker), model serving and APIs,&nbsp;CI/CD, and pipeline orchestration&nbsp;</li>

</ul>

<p><strong>Bonus Qualifications:</strong></p>

<ul>

<li>Fluency with actuarial methods and working with actuaries is a plus &nbsp;</li>

<li>Familiarity with healthcare&nbsp;and medical data&nbsp;</li>

<li>Familiarity with underwriting and claims, or predicting&nbsp;long-tailed&nbsp;and/or rare events&nbsp;</li>

</ul>

<p><strong>What We Offer:</strong>&nbsp;&nbsp;</p>

<ul>

<li>A fun, team-oriented startup culture.&nbsp;&nbsp;</li>

<li>Generous stock options - we all get to own a piece of what we’re building.&nbsp;&nbsp;</li>

<li>Unlimited vacation days.&nbsp;&nbsp;</li>

<li>Flexible schedule that supports working from home.&nbsp;&nbsp;</li>

<li>Full benefits package includes medical, dental, vision, 401k, paid paternal leave, and more.&nbsp;&nbsp;</li>

<li>Ample opportunities to learn and take on new responsibilities.&nbsp;&nbsp;</li>

</ul>

<p>We are an equal opportunity employer.&nbsp;</p>

<p>Salary Range: $140,000-170,000k base salary annually. </p>

<p>This role is also eligible for an annual performance bonus, equity grant, and a comprehensive benefits package. In accordance with&nbsp;the Massachusetts Pay Transparency Law, we are&nbsp;providing&nbsp;a good-faith salary range for this position at the time of posting. 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. If your salary expectations fall outside this range, we still encourage you to apply so we can have a conversation.&nbsp;</p>