Remote Data Scientist (Latin America)

About the role

Azumo, a San Francisco-based software company that builds production AI teams for clients worldwide, is hiring a Data Scientist. The role is fully remote across Latin America, aligned to the client's working day, and sits in the Data Scientist lane of Azumo's engineering organization. It focuses on turning a client's unmeasured problem into a model, a baseline and a number someone can act on.

Key responsibilities

• Define the question: turn a business decision into something measurable, including success criteria, baseline and expected improvement.
• Choose and apply methods and models, including supervised and unsupervised methods, CNNs and Transformers in PyTorch, and decide when a simpler model or no model is better.
• Fine-tune and adapt pretrained and open-weight models with LoRA, QLoRA or PEFT, and judge when fine-tuning is the wrong answer.
• Design baselines, holdouts and experiments, and report results with honest uncertainty.
• Analyze errors and hand over the model documented, with the metric that defines whether it is still working.
• Work inside the client's environment, including their repositories, standups and sometimes customer calls.

Required profile

• 5+ years building and validating models against real decisions, with Python as the primary language.
• Bachelor's or Master's degree in Computer Science, Data Science or a related field, or equivalent professional experience.
• Clear written and spoken English (C1 or above) and the confidence to explain technical trade-offs to a client.

Required skills

• Supervised and unsupervised methods, CNNs and Transformers, with hands-on PyTorch or an equivalent framework.
• Expert use of pandas, NumPy and scikit-learn.
• Statistics and experimental design, including baselines, holdouts and significance.
• Cloud experience with AWS, GCP or Azure and their AI services (e.g. SageMaker, Vertex AI, Azure Machine Learning).
• Active use of AI-assisted coding tools such as Claude Code, Cursor or GitHub Copilot.

Preferred: LLM evaluation, open-weight fine-tuning, multimodal work, causal inference or uplift modeling, MLOps tooling (MLflow, Weights & Biases, Kubeflow), and experience with SOC 2 or HIPAA compliance.

What we offer

• Paid time off (PTO) and U.S. holidays.
• AI training and mentored career development.
• Profit sharing.
• Remuneration in U.S. dollars.