Lead Data Scientist
Company: Octave
Location: Roanoke, VA (Remote)
Type: Full-time
Remote: Yes
Posted: 2026-08-05
About this role
Job Location (Short): Houston, Texas-USA | Madison, Alabama-USA | Roanoke, Virginia-USA
Workplace Type: Remote
Req Id: 2289
Responsibilities
Octave's ETQ
division is seeking a hands-on Data Scientist to build predictive models, implement Generative AI and Agentic AI features, and architect data-driven solutions for our document-based compliance management platform. This role requires a technical expert who can develop, deploy, and maintain ML systems in production environments.
- Build and deploy Generative AI features using foundation models (AWS Bedrock, OpenAI, Anthropic Claude) and RAG architectures with vector databases for compliance document understanding
- Design agentic AI systems that autonomously handle compliance workflows, document review, regulatory mapping, and multi-step reasoning tasks
- Implement comprehensive LLM evaluation frameworks with automated pipelines, custom metrics, benchmark datasets, and safety guardrails ensuring regulatory compliance
- Build end-to-end MLOps pipelines for model training, deployment, monitoring, versioning, and automated retraining with drift detection
- Develop predictive models for compliance risk scoring, regulatory change impact, anomaly detection, and time-series forecasting
- Write production-quality Python code for data processing, feature engineering, API development (FastAPI/Flask), and ETL/ELT workflows
- Lead A/B experiments and product analytics to measure AI feature impact and drive data-driven decision-making
- Create explainability frameworks (SHAP/LIME) and monitoring dashboards ensuring transparency and regulatory adherence
- Collaborate with cross-functional teams to translate business needs into ML solutions and communicate insights to stakeholders
Python (5+ years
): Production-level experience with Pandas, NumPy, scikit-learn, XGBoost, TensorFlow/PyTorch, Hugging Face Transformers, FastAPI/Flask, MLflow, and pytest
SQL:
Advanced proficiency with comp...