United States
Technology and data leader focused on data-driven solutions that deliver measurable business outcomes. Operates at the intersection of business and technology, aligning data/AI capabilities with organizational priorities to make data a competitive advantage. Passionate about building high‑performing teams and creating a scalable data ecosystem/culture that drives innovation.
Corient is a wealth management firm that delivers customized financial planning and investment services to clients, managing over $400 billion in client assets
• Led multi‑disciplinary data science, data engineering, and ML deployment teams, delivering on client and internal initiatives (e.g., development of digital twin to drive key supply chain decisions for a Fortune 500 company) • Drove the application of advanced analytics and AI across high‑value domains including personalization, customer segmentation, digital twins, supply chain optimization, workforce intelligence, and healthcare operations. • Advised executives, product leaders, and technical teams on end‑to‑end data strategy—covering architecture, infrastructure, use‑case prioritization, activation/piloting, and MLOps/change‑management best practices to ensure scalable/sustainable adoption. • Oversaw the development of predictive, forecasting, optimization, generative and segmentation models, leveraging a modern ML stack (sklearn, PySpark ML, XGBoost, PuLP, SHAP, Prophet, PyTorch, LangGraph/LangChain, SimPy)
• Led the technical design and development of the company’s recommendation engine microservice • Developed ETL processes to load data from multiple micro-services, Solr, Kafka topics and SQL databases into the company’s Neo4j knowledge graph database • Used graph-based KNN algorithm as well as NLP similarity-based content filtering to produce recommendations • Automated offline evaluation of recommendations using accuracy, novelty and diversity metrics • Worked with DevOps team members to deploy microservices across fleet leveraging Maven, Docker, Jenkins and Apigee
• Worked with Flask, React/Redux, Postgres & other technologies to take features from inception to production • Used best practices such as TDD, code reviews & continuous integration & deployment • Refined machine learning pipeline of NLP/MLP classifiers used to tag conversations to improve accuracy/consistency of predictions
• Built the company’s Django web API and React Native mobile app • Integrated third-party API and built data pipeline powering the company's core product • Partnered with Co-Founder to develop the company's budget and business plan