Supporting the advancement of weather and climate prediction for the energy and agricultural industries

Consulted clients on business initiatives involving SEO, marketing, website migrations, and data platforms, while overseeing the day-to-day client work delivered by a team of 4.• Increased membership sign-ups by 29% through targeted campaigns by automating customer segmentation based on product preferences using a KMeans clustering algorithm on PCA-processed data.• Achieved 99.7% accuracy in classifying gym exercises and counting reps by training and evaluating 7 ML models on fitness tracker data using Python, reducing gym time by 30% by eliminating manual tracking.• Reduced customer support request volume by 90% by developing, training, and deploying an AI chatbot that leveraged API calls to an Azure-hosted knowledge base containing 200+ FAQs, help tickets, and chat histories.• Generated 30+ new offer ideas for a client using large language models (LLMs) with Python and LangFuse with RAG-based prompt engineering.• Analyzed weather time-series data on Snowflake, visualizing temperature and precipitation trends on Power BI for a client that manages agricultural, energy, and commodity trading risks.• Used Power BI and Azure SQL to visualize ROI on content marketing for 3,000+ web pages for a Salesforce partner.• Achieved a 40% sales uplift in analytics courses by leveraging marketing analytics data and A/B testing.

Conducted business intelligence and competitive data analyses to inform B2B SaaS clients on the best paths forward for their Search Engine Optimization (SEO) strategies with evolving search engine algorithms. • Increased organic traffic by 86% in 4 months for a top sales community site by fixing technical SEO issues.• Delivered marketing intelligence analyses to an event software client, increasing traffic by 50% over 2 months.• Overhauled technical SEO for a Salesforce partner, raising user engagement despite search algorithm updates.

Obtained requirements from prospective clients and submitted proposals, and negotiated 4 contracts with clients over 6 months to write white papers, case studies, and RFP responses using statistical analyses and data visualizations.

Guided data-driven marketing strategy using product analytics while collaborating with a cross-functional team of 15.• Leveraged marketing analytics, exploratory data analysis, and A/B testing to inform product strategy, resulting in an uplift in sales of marketing analytics certification courses including Google Analytics, Google Ads, BigQuery, etc.• Built 30+ cross-channel campaigns and sales pipelines using historical customer behavior data in 2 years, while using analytics data to guide copywriting and offer creation for email subscribers and paid ads.

Guided the investment team’s decision-making on which wind farms to construct while managing 4 analysts and ensuring cross-functional collaboration between the development, finance, engineering, IT, and procurement teams.• Sped up data cleaning processes by 90x and increased predictive modeling accuracy by 40% by building a statistical wind analysis tool with C# and SQL, saving $120 million per year. • Conducted multiple wind resource assessments on the Meadow Lake Wind Farm from inception to an 800 MW project, now a key asset in the company portfolio that generates $75 million per year.• Performed predictive models of wind energy production on up to 20 GW in the company’s pipeline, helping the company secure power purchase agreements and wind project sales.

Engineered ETL pipelines and databases on Oracle cloud infrastructure, cutting data processing time from weeks to minutes, resulting in a 70% faster product launch cycle while reducing infrastructure costs by 55%.

Streamlined data pipelines, quality control and analysis processes, including troubleshooting technical barriers to improve the company’s speed-to-market and create a competitive edge.

Conducted daily meteorological analyses using numerical weather production model guidance, AirNow Tech web portal, atmospheric sounding forecasts, mathematical software, and data science to issue 3-day color-coded air quality forecasts for the Washington, DC metro area.

Investigated the requirements of the Advanced Weather Information Processing System (AWIPS) to build a database portal, improving NASA's operational efficiency in addressing extreme events and environmental incidents by 35%.

Architected a central Oracle database with airport and flight route data from the FAA. Built tools to interpret data graphically using ArcGIS, C++, .NET, Visual Basic, and UNIX.