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Big Data Engineer

Location:
Lynnwood, WA
Salary:
Open
Posted:
October 20, 2023

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Resume:

Yueying (Dee) Dai-Daniels

206-***-**** ad0h55@r.postjobfree.com Lynnwood, WA

SUMMARY OF SKILLS and QUALIFICATIONS :

Python(Proficient level)/SAS(Expert level)/SQL(Proficient level)

Objective: Seeking full time employment as Python Developer/Data Engineer/Data Analyst

Certified HBase Developing specialist in big data Hadoop Environment by using Java.

Proficient at developing BI for multi-dimensional slice/dice cubes for scheduling programs reports by using MS SQL Server and OLAP cubes.

Proficient at using Python and developed Machine Learnings for Language Models with Image models on the side.

Proficient at using Python for AI/Reinforcement Learnings for Business.

Proficient at using Python Operation Research applications for business including

Linear Programming simplex method,dual simplex method and Reduced Simplex

Method

Proficient at using Python for Transportation problems in the sense of Supply and Demand

(classic Economics Supply an Demand implementation in technologies)

such as Balancing,North Wester Corner/Simplex Method

Practiced using Python for other parts of Non-Linear programming such as integer Programming.

WORK EXPERIENCE

Cashier (Part time Employee)

Daiso Store,Lynnwood

Mar,2021 -Current

Marketing Strategist

(Volunteer Programs ) Jul, 2017 – Sept 2018

Everett Community College

Initialized/worked on building RESTful web Services with securities being considered by using Python Django related endeavors, Python FLASK for Calendar creations and Python Django for Higher Education focuses, and keeping informed with “ColdFusion UI the Right Way” with most updated JavaScript modules broadcasted by Open Sourced public domains.

Research and Develop Marketing Strategies for Campus Sustainability under Resource Conservation

Manager

Trouble shoot data analytics and developed algorithm to digitalize data by using technology through converting PDF files to Text Files then parsing and extracting key performance indicators from those text files for energy, renewed energy and waste management payment bills to reduce manual data entry for related business entities. Such technology could be applied to mortgages, hospitals and any firms who are using manual labors for data entry or interested to convert paper based data and use that data in all aspects of their businesses to do predictive analytics so as to drive business growth.

Marketing Researcher & Statistician Aug, 2008 – Dec, 2012

ADP/Cobalt, Seattle, WA

Served as lead statistician for the Business Intelligence group, executing analytics and marketing projects to inform critical business decisions with impacts to revenue, marketing strategy, and business operations

Key accomplishment: developed the Dealership Advertising Package (DAP) Cancellation Model:

Methodology: used Survival Model/Accelerated Failure Time (AFT) Model, and Logistic Regression Model

Created a predictive model to estimate the probability of cancellation of the DAP product subscription, a major source of revenue, using the DAP subscriptions web analytics data, site performance data, and behavioral data from employees assigned to the accounts

Created a secondary behavioral model to predict the probability of retaining the product, given employee attributes and aptitudes

Result: my models successfully isolated key risk factors for cancellation and directly produced changes in how ADP/Cobalt sold and managed the DAP program, resulting in significant cost savings for my firm.

Other projects and highlights:

Designed and administered a “Pre/Post” Survey to measure a respondent’s behavioral intent before and after the respondent’s visit to a specific website

Assessed consumer/user experience by testing hundreds of web pages, site sections, and site features to determine which individual page influenced behavioral intent (after deriving several thousand variables from those features).

Developed a custom segmentation algorithm based on brand and model preferences, buyer readiness level, shopper type (i.e. vehicle buyer vs. parts and services buyer), etc.

Developed a custom search phrase parsing algorithm; by using both exact-match and fuzzy-match algorithms, my work product grouped the search phrase so that paid search produced a better conversion rate and a lower bounce rate

Senior Analyst, Financial Engineering Jul, 2007 – Jul, 2008

Washington Mutual Bank, Seattle, WA

Built Logistic Regression Models for Commercial Real Estate Mortgages and Commercial Lending Mortgages to estimate the probability of 90+ days of delinquency, severity, and corresponding loss

Developed Discount Cash Flow process to estimate loss for Trouble Debt Restructuring accounts for Residential Mortgages

Risk Analyst, Business Intelligence Engineer II Nov, 2004 – Apr, 2007

Amazon, Seattle, WA

Conducted expert data analysis using the Proc Logistic Regression SAS Method, with a focus on using Proc Logistic for scorecard modeling and Decision Tree/Enterprise Miner for Segmentation and Failed Rule analysis

Used Perl for actual model implementation and took ownership of monitoring the failed queue daily volume to adjust the score threshold, in order to accommodate the work load and capacities of fraud investigators for the Japan website (both retail and marketplace)

Accounted for the total dollar amount of customer orders (revenue) and the prescreen score in order to optimize the best cutoff to minimize both the false positive ratio and to maximize fraud dollar return

Key projects and accomplishments:

Built custom fraud detection models focusing on domestic and international transactions and across multiple types of consumer segments and risk levels

Built Deutschland Marketplace, Japan, and U.S. + U.O.P convergence fraud detection models

Built and collaborated with engineers to implement fraud detection models for U.S. retail group across multiple consumer segments and dollar risk levels

Statistician Apr, 2002 – Oct, 2004

T-Mobile, USA Bellevue, WA

Built various databases through creating ETL processes and Fact/Dimensional tables to support OLAP Cubes that I had developed by using Microsoft SQL Server/Analytics Services and Published web reporting cubes through VBScript and PHP for Portfolio Risk Management department, Churn Models, and Application Volume forecasting model by using SAS/ETS

Validated a few statistical models from credit bureaus

SAS Programmer Analyst Mar, 1998 – Jan, 2001

Group Health Cooperative of Puget Sound, Seattle, WA

Tested production programs and macros to determine if they were Y2K compliant then wrote macros

to replace those that were non-compliant.

Developed and enhanced web based decision support application by writing Stored Procedures in sybase, updated JavaScripts managed/maintained Behavioral Health departmental IIS Serve by using SQL and paper based ad hoc report by SAS and Access/VBA.

Proficient in Sybase/SQL, SAS (SQL, Macro, Base) and HTML. Maintained relational database.

Economist

The People’s Bank of China, Wuhan, Hubei, China 1985 – 1995

EDUCATION

Continuing Education, Mukilteo, WA 2013 to Jun 2017

Successfully completed certification as a Cloudera Certified Specialist in Apache HBase (CCSHB, CDH Version 5) to design distributed system for real-time analytics in both predictive and descriptive dimensions

HBase training course with Cloudera University (Java Core)

Hadoop Developer course with Cloudera University (Java Core)

Hadoop/Hive/Pig course for Data Analysts with Cloudera University

Hadoop/Python/R/Hive/Pig course for Data Science with Cloudera University

University of Washington, Seattle, WA

M.A. in Economics, Econometrics Concentration

Wuhan University, Wuhan, Hubei, China

B.A. in Economics



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