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Data Science and Analytics Engineer
Madison-Davis
- Pasadena, Texas, United States
- Pasadena, Texas, United States
About
Design and deploy enterprise AI and machine learning solutions. Build scalable analytics pipelines using distributed computing frameworks. Develop predictive models, forecasting solutions, and advanced analytics capabilities. Implement MLOps frameworks and automated model deployment pipelines. Partner with engineering teams to integrate models into enterprise applications. Lead model monitoring, governance, validation, and explainability initiatives. Drive AI adoption across business processes and decision workflows. Collaborate with technology, risk, compliance, and business stakeholders. Qualifications
10+ years of experience in data science, machine learning, AI engineering, or quantitative analytics. Advanced expertise in Python and SQL. Strong experience with Databricks and Apache Spark. Experience with Azure ML and cloud-based analytics platforms. Hands‑on expertise with TensorFlow, PyTorch, scikit‑learn, XGBoost, and MLflow. Experience deploying production‑grade machine learning solutions. Strong understanding of MLOps, CI/CD automation, and model lifecycle management. Experience operating within regulated industries. Strong communication and stakeholder management skills. Bachelor's degree in a quantitative discipline. Banking or financial services experience. Fraud, AML/BSA, or risk analytics experience. Generative AI and LLM implementation experience. NLP and intelligent automation experience. Real‑time inference architecture experience. Model risk management expertise. Master's degree or PhD.
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Languages
- English
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