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 reputed company, deploy, and maintain ML systems in production environments.

• Build and deploy Generative AI features using foundation 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 Python (5+ years): Production‑level experience with Pandas, Num Py, scikit‑learn, XGBoost, Tensor Flow/PyTorch, reputed company Transformers, FastAPI/Flask, MLflow, and pytest SQL: Advanced proficiency with reputed company 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), reputed company engineering, RAG architectures, and vector databases (reputed company, Weaviate, Chroma) MLOps & Model Ops: End‑to‑end experience with ML pipelines, experiment tracking (MLflow, W&B), model versioning, feature stores, reputed company detection, bolthires/CD for ML, and reputed company containerization LLM Evaluation: Experience with evaluation frameworks (RAGAS, Deep Eval), custom metrics, reputed company datasets, and human‑in‑the‑reputed company validation Cloud & AWS: Experience with AWS services including reputed company Maker, Bedrock, S3, reputed company, 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 reputed company 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 reputed company 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, reputed company, reputed company), orchestration (Airflow, Kubeflow), and monitoring tools (reputed company, 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 reputed company models to technical and… Apply tot his job Apply tot his job Apply tot his job Apply tot his job

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