Principal Data Scientist

Gradient AI

Principal Data Scientist building advanced predictive models for Gradient AI’s insurance decision-intelligence platform. Leading modeling strategy, MLOps standards, and high-impact analytics using deep learning and large language models.

Posted 8/4/2026full-timeRemote • Massachusetts • 🇺🇸 United StatesLead💰 $190,000 - $235,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in deep learning, machine learning algorithms, and the Python data science ecosystem, with a strong focus on MLOps practices and model lifecycle management. Capable of leading complex modeling initiatives and effectively communicating insights to diverse stakeholders.

Highest-signal resume keywords

Deep LearningMachine Learning AlgorithmsMLOps Lifecycle ManagementPredictive ModelingPython Data Science Ecosystem

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Predictive ModelingDeep LearningMachine Learning AlgorithmsNatural Language ProcessingXGBoostTransformersGLMsTime Series AnalysisSequence ModelingFederated Learning

Soft Skills

Strong Communication SkillsCollaboration Skills

Tools & Technologies

MLOps StandardsData Science FrameworksModel Monitoring Tools

Industry Keywords

Healthcare DataMedical DataActuarial MethodsUnderwritingClaims Management

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Lead the organization’s most complex and high-impact modeling and analytical initiatives
Set modeling strategy across the organization
Drive novel data science work and raise technical standards for building and shipping models
Combine deep learning, large language models, and traditional data science techniques to create hybrid models
Brainstorm, prototype, prove, deploy, and rapidly realize the market value of projects
Solve problems involving big data, federated learning, unstructured data, time series, sequence modeling, GLMs, XGBoost, and Transformers
Communicate data insights to customers, stakeholders, and prospects to drive business results
Spearhead new projects and build reusable systems, packages, and frameworks
Create team MLOps standards and practices
Monitor model drift, KPIs, and impact; drive improvements, triage issues, and manage technical debt

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Data Science, Biostatistics, Mathematics, or a related field and 8+ years of professional data science experience building predictive models, or a Master’s or Ph.D. and 5+ years of such experience
Expert-level knowledge of deep learning, machine learning algorithms, and the core Python data science ecosystem
Strong communication and collaboration skills, including communicating with nontechnical stakeholders and leadership
Deep experience with natural language, medical data, long-tail predictions, or similar problem spaces
Strong familiarity with all phases of the MLOps model lifecycle
Experience creating team standards and practices to enforce quality and speed
Deep experience being accountable for long-term model impact, including MLOps pipelines, drift monitoring, KPI and impact monitoring, incremental and long-term improvements, issue triage, and responsible technical-debt management
Fluency with actuarial methods and experience 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

Comp & perks

Generous stock options
Unlimited vacation days
Flexible schedule that supports working from home
Medical, dental, and vision benefits
401k
Paid paternal leave
Annual performance bonus
Comprehensive benefits package
Opportunities to learn and take on new responsibilities
Merit-based increases, promotions, and company-wide compensation adjustments