Wrote the most complex ETL (Extract / Transform / Load) processes, designs database systems, and developed tools for real-time and offline analytic processing. Troubleshoot software and processes for data consistency and integrity. Led the integration of highly complex and large-scale data from a variety of sources for business partners to generate insight and make decisions.
Developed queries and performed extensive programming to access, transform, and prepare data for statistical modeling. Structured and translated requirements into an analytic approach.
Delivered ML project to customers from conception to completion by overseeing business need, aggregating data, exploring data, building & validating predictive models, and deploying completed models with concept-drift monitoring and retraining. Utilized AWS AI services (Personalize), ML platforms (SageMaker), and frameworks MXNet, TensorFlow, PyTorch, SparkML, scikit-learn) to help customers build ML models.
Assess key parameters using SQL and Python to drive product development with insightful analysis and collaboration. Maintain dashboards and data warehouses to quickly deliver information. Evaluate existing practices for efficacy and accuracy.
Develop insights and data visualizations to maximize opportunity and increase efficiency. Prepare monthly reports for management and key stakeholders. Translate complex data models to understandable written narratives for ad hoc information requests.
Discover novel insights using SQL and Python databases. Collaborate with project management and sales to create effective strategies addressing client needs and product development. Prepare and present annual revenue forecasts to C-suite managers and key stakeholders. Conduct financial and market research to produce automated tools and support company initiatives.