SUMMARY:

• Data Scientist with more than 10 Years of industry experience Extensive experience in application of predictive modeling and segmentation techniques to address business needs. More than ten years of experience in leveraging machine learning and predictive modeling algorithms for marketing in telecommunications, consumer goods, people analytics and scientific and market researches. Recognized as team lead contributing to incremental revenues through deployment of machine learning and statistical models for customer lifecycle management (from acquisition to retention). Excellent project management skills and collaboration with internal business partners and vendors. Ability to solve business problems and proven track record in measuring or monetizing model results related to customer satisfaction and experience, revenue generation and cost reduction. Proficient and extensive use of top of the line statistical and business intelligence solutions such as R, SAS, SPSS, Tableau and SQL. Working knowledge of Python. Applied conspicuous and strategic statistical methodologies to massive data and ability to translate trend and patterns to meaningful business insight to support important business decisions. Comprehensive verbal and written communication skills through clear and concise presentation of results and data - driven recommendations. Passionate in data and in learning and leveraging new predictive modeling algorithms in discovering trends and business opportunities. Has creative eyes in summarizing data.
• Published papers in several international journals and acknowledged internationally the contributions to agricultural and social researches.
• In 2015, co-authored a publication in Science and Public Policy as an independent collaboration with a science community.
• Expecting certification in R and Python programming languages.
• Reduced Confidential ’s customer service calls by 10% annually, estimated at USD 5 million cost reduction using predictive models, segmentation and sequence analysis. Improved customer experience by leveraging behavior patterns and improved billing and call center operations.
• Pioneered Customer Lifecycle Management for Confidential in Philippines and contributed in achievement of USD 20 million incremental revenue through implementation of more than 50 predictive models for Marketing Analytics (e.g. Acquisition, Customer Segmentation, Cross-sell and Up-sell, Churn).
• Created Nvidia’s Employee Experience and Engagement landscape using Structural Equation Model. The model served as a tool to understand the dynamics of employee satisfaction and loyalty. Reduced coding time for open-ended responses in the employee survey by 50% through application of text mining and multiple response classification techniques.
• Developed Cisco’s acquisition models for 15 regions to identify new markets. Improved cross-sell and up-sell models for more than 100 markets by including text mining, gradient boosting and random forest models.
• Improved retail market indicators for Confidential specific to price of survey products by setting 0.03 to 0.05 standard error based on statistical simulation using gamma distribution.
• Contributed to achievement of 77% increase in weight of Tilapia, a remarkable advancement in the field of fish genetic research.
• International speaking engagements and co-authorship and acknowledgements in more than 10 journal publications.

PROFESSIONAL EXPERIENCE:

Confidential, San Francisco, CA

Senior Data Scientist

Responsibilities:

• Customer Experience: Developed prescriptive and predictive models combined with various text analytics algorithms from call center notes, web and chat channels and identified priority areas for call reduction. Profiled customers likely to have repeated calls with similar concerns and leveraged the behavioral patterns for tactical recommendations and strategic direction for operational improvement. Models were developed in SAS and R.
• WiFi Usage Optimization: Monetized WiFi usage data (millions of records daily) and market research data and developed and evaluated metrics such as usage per household or per device, usage per session, usage throughput, access point (AP) geographic information that potentially improved customer experience and increased customer satisfaction. Identified customers likely to recommend the brand to family and relatives.
• Ad targeting: Analyzed customer viewership patterns for ad targeting and monetization. Collaborated with big data engineering for deployment validation in Flume/Kafka/Storm/Hadoop.
• Recommendations, results and insights communicated and presented to senior management team and contributed in the planning discussions for operational improvements.

Confidential, Santa Clara, CA

Data Scientist

Responsibilities:

• Led HR Analytics and identified top 10% talents likely to leave the company through predictive modeling. Estimated attrition rate was used and reported to Dow Jones Sustainability Index. Extensive collaboration with HR Business Partners to leverage robust employee behavior analyses.
• Executed 50% reduction in turnaround time of employee engagement survey’s open-ended question analysis by applying text mining and multiple logistic regression modeling.
• Identified adequate employee and manager conversation topics using logistic regression.
• Designed total picture of Nvidia’s employee engagement and employee experience using Structural Equation Modeling (SEM).

Confidential, San Jose, CA

Statistical Analyst

Responsibilities:

• Supported approval of business use case (i.e. Angoss Text Mining Software investment) through development of new predictive models incorporating Customer Satisfaction (CSAT) data into current Customer Registry data.
• Developed Acquisition Models for Cisco’s 15 Regional markets and identified new markets.
• Delivered monthly operational Cross-sell and Upsell Predictive models scores for 15 regions, 84 countries for 49 products and technologies. Improved models using gradient boosting and random forest model.

Confidential, Pleasanton, CA

Senior Research Analyst

Responsibilities:

• Established forecasting methodology and data cleaning for U.S. consumers’ total bill payments and estimated consumer’s adoption and market sizing of mobile applications and online shopping and payments through app or browser. Improved accuracy of forecasts by 10%.
• Reviewed presentation materials for clients and ensured that insights presented give business value or create new opportunities.

Confidential, Philippines

Business Analytics Manager

Responsibilities:

• Initiated and led the company's multi-year Business Analytics roadmap and led 2 System Development Projects.
• Improved accuracy of sales forecasts and achieved 3% incremental revenue using advanced autoregressive models.

Confidential

Data and Systems Manager

Responsibilities:

• Established the Confidential Marketing Analytics.
• Increased customer retention by 30% through predictive modeling.

Confidential, Philippines

Confidential Statistical Modeling Department Head

Responsibilities:

• Led and pioneered the Customer Lifecycle Management Project and contributed in the achievement of USD 20 million through execution of targeted marketing campaigns using more than 50 statistical models for Marketing Analytics using SAS Enterprise Miner (e.g. Customer Segmentation, Predictive models on Churn and other Campaigns, Cross-sell and Up-sell, Market Basket Analysis, etc.).
• Supervised mentored and developed 4 statistical modelers and SAS programmers.

Confidential, Philippines

Consultant

Responsibilities:

• Led survey operations and calibrated sampling design.
• Reduced store claimed price error rate by 10% by establishing price bounds of all product categories based on a statistical simulation process.

Confidential, Philippines

Statistician/Assistant Scientist

Responsibilities:

• Contributed in the achievement of 77% increase in weight of Confidential through extensive analyses of experimental data using mixed-effects model.
• Belong to the top 20% of high-performing Scientists who transitioned the Headquarters from the Philippines to Malaysia.