Principal Data Scientist; AI- REMOTE; US), Sales

Position: Principal Data Scientist (AI)- REMOTE (US), Sales Principal Data Scientist (AI) - REMOTE (US) Job Location (Short): Houston, Texas-USA | Madison, Alabama-USA | Roanoke, Virginia-USA. Workplace Type: Remote. Business Unit: ALI-ETQ. Req . Responsibilities Hexagon'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, Num Py, scikit‑learn, XGBoost, Tensor Flow/PyTorch, Hugging Face Transformers, FastAPI/Flask, MLflow, and pytest SQL: Advanced proficiency with complex queries, window functions, and optimization Machine Learning & NLP: Strong foundation in supervised/unsupervised learning, deep learning, document understanding, text classification, and semantic analysis Generative AI & LLMs: Hands‑on experience with foundation models (GPT, Claude, Llama), prompt engineering, RAG architectures, and vector databases (Pinecone, Weaviate, Chroma) MLOps & Model Ops: 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 LLM Evaluation: Experience with evaluation frameworks (RAGAS, Deep Eval), custom metrics, benchmark datasets, and human‑in‑the‑loop validation Cloud & AWS: Experience with AWS services including Sage Maker, Bedrock, S3, Lambda, EC2, and Cloud Watch Statistics & Experimentation: Strong foundation in statistics, A/B testing, causal inference, and experimental design Visualization: Proficiency with Tableau, Power BI, or Python visualization libraries Education / Qualifications Experience & Education • 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) • Track record of deploying ML systems processing large‑scale datasets with proper monitoring and governance Preferred Qualifications • Experience with agentic AI frameworks (Lang Graph, Lang Chain, Auto Gen, 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… Apply tot his job