Lead Data Scientist

Responsibilities

• 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.
• Develop end-to-end MLOps pipelines for model training, deployment, monitoring, versioning, and automated retraining with drift detection.
• 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.

Requirements

• Production-level experience with Pandas, NumPy, scikit-learn, XGBoost, TensorFlow/PyTorch, Hugging Face Transformers, FastAPI/Flask, MLflow, and pytest.
• Advanced proficiency with complex queries, window functions, and optimization.
• Strong foundation in supervised/unsupervised learning, deep learning, document understanding, text classification, and semantic analysis.
• Hands-on experience with foundation models (GPT, Claude, Llama), prompt engineering, RAG architectures, and vector databases (Pinecone, Weaviate, Chroma).
• End-to-end experience with ML pipelines, experiment tracking (MLflow, W&B), model versioning, feature stores, drift detection, CI/CD for ML, and Docker containerization.
• Experience with LLM evaluation frameworks (RAGAS, DeepEval), custom metrics, benchmark datasets, and human-in-the-loop validation.
• Experience with cloud services including AWS services such as SageMaker, Bedrock, S3, Lambda, EC2, and CloudWatch.
• Strong foundation in statistics, A/B testing, causal inference, and experimental design.
• Proficiency with Tableau, Power BI, or Python visualization libraries.

Qualifications

• 7+ years in data science, ML engineering, or related roles.
• 3+ years building NLP/generative AI applications and implementing MLOps in production.
• Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or related field (PhD preferred).

Preferred Qualifications

• Experience with agentic AI frameworks (LangGraph, LangChain, AutoGen, CrewAI).
• Knowledge of Life Sciences/regulated industries (FDA, EMA, ISO, GxP) and compliance management systems.
• Familiarity with big data tools (Spark, Databricks, Snowflake), orchestration (Airflow, Kubeflow), and monitoring tools (Datadog, Prometheus).
• Experience with LLM fine-tuning, document processing libraries, multi-modal AI, or distributed training.
• Understanding of ML governance, bias detection, model risk management, and data privacy regulations (GDPR, CCPA, HIPAA).
• Experience working in agile environments with Jira.
• AWS ML certifications or similar credentials.

Key Competencies

• Strong communication skills explaining complex models to technical and non-technical audiences.
• Proven ability to convert POCs into production-grade solutions.
• Understanding of ethical AI and building trustworthy, explainable systems for regulated environments.

About Octave

Octave provides mission-critical software that empowers organizations to make informed decisions across every stage of the asset lifecycle — Design, Build, Operate and Protect — where performance, safety, and reliability are non-negotiable and failure is not an option. Turning complex operational data into actionable intelligence, Octave connects expertise, real-world conditions and enterprise-scale insight to improve performance, resilience and incident response where it matters most. Octave has approximately 7,200 employees in 45 countries. Learn more at octave.com and follow us on LinkedIn.