# Staff Data Scientist

**Company:** [Gradient AI](https://hotfix.jobs/companies/gradient-ai)
**Location:** Remote
**Role:** Data Science
**Experience:** 7+ years
**Skills:** Python, R, jupyter, Deep Learning, Transformers, neural networks, LLMs, MLOps, Docker, model serving, CI/CD, xgboost, federated learning, time-series modeling, pipeline orchestration
**Posted:** 2026-08-04

> Leads complex predictive modeling and analytical initiatives using deep learning, large language models, and traditional data science methods. The role requires 5+ years of experience with a bachelor’s degree or 3–5 years with an advanced degree, plus production MLOps and peer leadership experience.

## Job Description

## Responsibilities
- Lead complex modeling and analytical projects of broad and diverse scope.
- Drive cross-product initiatives with minimal direction and set technical approaches for ambiguous problems.
- Apply deep learning, large language models, and traditional data science techniques to create hybrid models.
- Brainstorm, prototype, validate, deploy, and realize the value of models quickly.
- Work with big data, federated learning, unstructured data, time-series and sequence modeling, GLMs, XGBoost, and Transformers.
- Communicate data insights clearly to customers, stakeholders, and prospects.
- Take initiative and spearhead new projects.
- Build reusable systems, packages, and frameworks that elevate the data science team.
- Mentor junior data scientists and improve team standards.

## Requirements
- Bachelor's degree in Computer Science, Data Science, Biostatistics, Mathematics, or a related field and **5+ years** of professional data science experience building predictive models; **or** a master's or Ph.D. in a related field and **3–5 years** of professional data science experience building predictive models.
- Advanced proficiency with deep learning frameworks and the core Python data science ecosystem.
- Deep understanding of modern AI architectures, including Transformers, neural networks, and large language models.
- Strong technical communication and collaboration skills, including communication with nontechnical stakeholders and collaboration with engineering and product teams.
- MLOps experience taking models from notebooks to production, including experiment tracking, packaging, Docker containerization, model serving and APIs, CI/CD, and pipeline orchestration.
- Experience monitoring production models for data drift, concept drift, performance degradation, and alerting.
- Strong peer leadership and mentoring skills.

## Nice-to-haves
- Fluency with actuarial methods and experience working with actuaries.
- Familiarity with healthcare and medical data.
- Familiarity with underwriting and claims, or predicting long-tailed and rare events.

## Compensation and Benefits
- Generous stock options.
- Unlimited vacation days.
- Flexible schedule supporting work from home.
- Medical, dental, and vision insurance.
- 401(k).
- Paid parental leave.
- Opportunities to learn and take on new responsibilities.

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