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Gradient AIGradient AIUnited States

Senior Data Scientist

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.

Salary not listed
Remote5+ YOEData Science

About the role

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.

Skills

PythonPyTorchTensorFlowTransformersLLMsneural networkspandasNumPyscikit-learnlightgbmSQLAWSDockerCI/CDMLOps

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