I greatly enjoy bridging the gap between science, technology and business. I believe that emerging technology can provide positive change to professional and personal lives. Excels in a remote setting, with a proven trac…
I greatly enjoy bridging the gap between science, technology and business. I believe that emerging technology can provide positive change to professional and personal lives. Excels in a remote setting, with a proven track record in tech leadership and sales consulting for advanced data solutions. Currently pursuing advanced knowledge in AI and Machine Learning to further enhance big data warehouse project capabilities.
● Constructed a Machine Learning forecasting tool that increased data management and forecasting accuracy within Azure Cloud Services.
● Utilized Databricks platform for scalable data processing and expanded strategies into the Philippines market.
● Enhanced developer productivity through efficient data management and accurate forecasting methods.
● Cultivated a remote work environment and led tech initiatives towards advanced data solutions
Developed and maintained Indonesia CPFR platform, leveraging Databricks for enhanced data management and forecasting accuracy.
Orchestrated the expansion of the CPFR platform into the Philippines market, employing Databricks to streamline consumer goods sellout forecasting with ensemble and deep learning methods.
Constructed a Proof of Concept (POC) Machine Learning forecasting tool within Azure Cloud Services, integrating Databricks for scalable data processing.
Tools: Python, Spark, SQL, Databricks, AML, ADF
Directed AI initiatives for Fortune Global 100 and 500 companies, emphasizing the utilization of Databricks for end-to-end machine learning system development in the cloud.
Played a pivotal role in Databricks implementations, focusing on data quality, lineage, and governance in big data warehouse projects.
Tools: Python, Spark, SQL, Databricks, AML, ADF, LightGBM, XGBoost, Elastic Net, AWS Sage Maker
Worked on developing ML models to derive knowledge from past counseling sessions recordings
Pioneered ML model development using Databricks for analyzing counseling session recordings to derive actionable insights.
Based on quantitative analysis developed python based counselor-patient matchmaking algorithm based on past client intake forms extracting data points with OCR and counsel success rate across different types of disorders
Part of a team working on Depression Risk Prediction in Children using ML
Created probability-weighted payment stream valuation model with risk-adjusted discount rates for leveraged buyouts and unleveraged payouts
Proposed algorithmic research solutions to improve automatic lead generation process from public records and existing court cases database using OCR and then extracting meaning with NLP machine learning
Developed a pricing model based on different payment stream scenarios; further developed an automated discounting tool with integrated DCF analysis and regression modeling
Using OCR extracted keywords from customer's health report and created risk score scale based on past records analysis to determine the optimal payment stream length for desired return and investor's risk appetite
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