# Senior Data Scientist

**Company:** [Gradient AI](https://hotfix.jobs/companies/gradient-ai)
**Location:** Remote
**Role:** Data Science
**Experience:** 5+ years
**Skills:** Python, PyTorch, TensorFlow, Transformers, LLMs, neural networks, pandas, NumPy, scikit-learn, lightgbm, SQL, AWS, Docker, CI/CD, MLOps
**Posted:** 2026-08-04

> Develop and deploy predictive AI models using deep learning, large language models, and traditional data science methods. The role requires strong Python skills, production MLOps experience, and a bachelor's degree with 3–5 years of experience or an advanced degree with less experience.

## Job Description

## Responsibilities
- Advance core AI models and drive them to market in collaboration with data science, product, and engineering partners.
- Own well-scoped models end-to-end and independently ship measurable improvements to product AI capabilities.
- Combine deep learning, large language models, and traditional data science techniques to create hybrid models.
- Brainstorm, prototype, validate, deploy, and realize the market 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 to support business outcomes.
- Take initiative on ambiguous projects and build reusable systems, packages, and frameworks for the team.

## Requirements
- Bachelor's degree in Computer Science, Data Science, Biostatistics, Mathematics, or a related field and 3–5 years of professional data science experience building predictive models; **or** a master's or doctoral degree in a related field and 1–2 years of such experience.
- Comprehensive hands-on experience with deep learning frameworks such as PyTorch or TensorFlow and modern AI architectures, including Transformers, neural networks, and LLMs.
- Advanced proficiency in Python and its core data science ecosystem, including Pandas, NumPy, Scikit-learn, and LightGBM.
- Strong technical communication and collaboration skills within agile squads and data science leadership.
- Familiarity with SQL, relational databases, and cloud environments such as AWS, Azure, Google Cloud, or Databricks.
- MLOps experience taking models from notebooks to production, including experiment tracking, packaging, containerization with Docker, model serving and APIs, CI/CD, and pipeline orchestration.

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

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

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