Remote Data Jobs

• Define and drive the long-term roadmap for our data ecosystem.
• Build and lead a best-in-class team across Data Engineering, Analytics Engineering, and future Data Science/ML Engineering.
• Architect data foundations that support ML and AI workloads.

Work on KBRA's financial analytical system. Collaborate with technical and non-technical counterparts to learn the domain and its unique challenges. Develop, build, run, and support the system in collaboration with other engineering, design, product, and platform teams.

• Design and develop the whole GCP data ecosystem, including Cloud Storage, Cloud Functions, and BigQuery.
• Guide and mentor the data engineering team, providing technical direction and ensuring adherence to best practices.
• Design and optimize data storage architectures, including data lakes and data warehouses.

Collaborate with stakeholders to understand business requirements and translate them into data engineering solutions. Design and oversee the data architecture and infrastructure, ensuring scalability, performance, and security. Create scalable and efficient data processing frameworks, including ETL processes and data pipelines.

• Define analytical strategy and govern key metrics.
• Architect scalable data models and lead cross-functional initiatives.
• Communicate analytical findings through compelling narratives.

Manage, analyze, and transform complex biomedical and clinical data to support research and decision-making. Implement robust data pipelines, quality control procedures, and reporting tools. Collaborate with cross-functional teams to design data collection instruments and develop dashboards.

• Engage with advanced topics across probability theory, measure theory, real and functional analysis, optimization, abstract algebra, and category theory.
• Challenge cutting-edge AI systems with complex proofs, evaluate mathematical reasoning for correctness and rigor, and identify subtle conceptual or logical failures that only trained mathematicians can catch.
• Converse with the model on theoretical problems, construct and evaluate proofs, analyze reasoning steps for validity, articulate failure modes, and collaborate with our team to refine prompts, evaluation frameworks, and mathematical reasoning benchmarks.

Evaluate diverse drone images and apply strict annotation standards. Isolate the core structure of a drone while excluding peripheral elements. Distinguish between structural and non-structural features across varied drone designs, lighting conditions, and environments.

• Partner with stakeholders to translate business challenges into data science problems.
• Own the end-to-end lifecycle of data science models, from data exploration to deployment.
• Develop scalable and efficient models, balancing algorithmic complexity with business needs.

• Drive the development of next-generation foundation models for wearable biosignals that power Oura’s health sensing features.
• Design and validate deep learning approaches for large‑scale wearable time-series and running rigorous evaluations on research and clinical datasets.
• Partner with cross‑functional teams to translate evidence into shipped features and scientific publications.