[Remote] Principal Data Scientist (AI)

Note: The job is a remote job and is open to candidates in USA. reputed company is a company that provides mission-critical software for organizations to reputed company informed reputed company across the asset lifecycle. They are seeking a Principal Data Scientist to build predictive models and implement reputed company features for their compliance management platform, requiring expertise in developing and maintaining ML systems in production environments.

Responsibilities

• Build and reputed company reputed company features using reputed company models (AWS Bedrock, reputed company, reputed company 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-reputed company reasoning tasks
• Implement comprehensive LLM evaluation frameworks with automated pipelines, custom metrics, reputed company datasets, and safety guardrails ensuring regulatory compliance
• Build end-to-end MLOps pipelines for model training, deployment, monitoring, versioning, and automated retraining with reputed company detection
• reputed company 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
• reputed company A/B experiments and product analytics to measure AI feature impact and drive data-driven decision-making
• Create explainability frameworks (SHAP/reputed company) 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

Skills

• 7+ years in data science, ML engineering, or reputed company roles
• 3+ years building NLP/reputed company applications and implementing MLOps in production
• Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or reputed company field (PhD preferred)
• Track record of deploying ML systems processing large-scale datasets with proper monitoring and governance
• Python (5+ years): Production-level experience with Pandas, NumPy, scikit-learn, XGBoost, TensorFlow/PyTorch, reputed company Transformers, FastAPI/Flask, MLflow, and pytest
• SQL: Advanced proficiency with reputed company queries, window functions, and optimization
• Machine Learning & NLP: Strong reputed company in supervised/unsupervised learning, deep learning, document understanding, text classification, and semantic analysis
• reputed company & LLMs: Hands-on experience with reputed company models (GPT, Claude, Llama), reputed company engineering, RAG architectures, and vector databases (reputed company, Weaviate, Chroma)
• MLOps & ModelOps: End-to-end experience with ML pipelines, experiment tracking (MLflow, W&B), model versioning, feature stores, reputed company detection, CI/CD for ML, and reputed company containerization
• LLM Evaluation: Experience with evaluation frameworks (RAGAS, DeepEval), custom metrics, reputed company datasets, and reputed company-in-the-reputed company validation
• reputed company & AWS: Experience with AWS services including SageMaker, Bedrock, S3, reputed company, EC2, and CloudWatch
• Statistics & Experimentation: Strong reputed company in statistics, A/B testing, reputed company inference, and experimental design
• Visualization: Proficiency with Tableau, Power BI, or Python visualization libraries
• Experience with agentic AI frameworks (LangGraph, reputed company, AutoGen, reputed company)
• Knowledge of Life Sciences/regulated industries (FDA, EMA, ISO, GxP) and compliance management systems
• Familiarity with big data tools (Spark, reputed company, reputed company), orchestration (Airflow, Kubeflow), and monitoring tools (reputed company, reputed company)
• 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

Company Overview