onsite
Data Scientist - Extensions - Fundamental
Data Scientist
Data Scientist focused on extending Fundamental's Large Tabular Model platform, building predictive pipelines, and delivering AI‑driven insights for enterprise decision‑making using Python, deep learning frameworks, and cloud services.
About the role
Key Responsibilities
- Design, develop, and fine‑tune extensions for the Large Tabular Model (LTM) to address diverse enterprise use cases.
- Build end‑to‑end machine‑learning pipelines, from data ingestion and preprocessing to model training, evaluation, and deployment.
- Collaborate with product and engineering teams to translate business requirements into scalable AI solutions.
- Conduct experiments, perform statistical analysis, and iterate on model performance using Python and deep‑learning libraries.
- Deploy and monitor models on cloud infrastructure (AWS), ensuring reliability, security, and cost‑effectiveness.
Requirements
- Strong proficiency in Python and experience with PyTorch or TensorFlow for building deep‑learning models.
- Hands‑on experience with large‑scale tabular data, SQL, and data‑engineering pipelines.
- Demonstrated ability to develop, evaluate, and productionize machine‑learning models in a cloud environment (AWS preferred).
- Solid understanding of statistical methods, model validation, and performance optimization.
- Excellent problem‑solving skills and the ability to communicate technical concepts to non‑technical stakeholders.
Skills
pythonpytorchtensorflowmachine learningsqlaws