Data Insurance

Don Wang 905-***-**** Email:*********@*******.***

OBJECTIVE: Business Analyst

QUALIFICATIONS

• Extensive experience of statistics analysis, data mining, modeling, technical reporting within insurance,

banks, marketing, and manufacturing industries.

• Proficient knowledge in loyalty, profiling, segmentation, pre/post campaign, retention, risk management.

• Strong data mining/modeling skills in linear regression, logistic regression, decision tree, and survival

analysis.

• Extensive practice about pre-campaign strategy design, post-campaign assessment, and troubleshooting.

• Well developed skills about SAS in different Operating System like Mainframe, UNIX, Linux, Windows,

etc.

• Profound SAS skills with SAS modules like: Base, Stat, SQL, Macro, Access, Graph, Enterprise Miner,

Enterprise Guide, OLAP, Assist, ETS, OR, AF, etc.

• Proved skills in requirements verification, project process design, implementation, result evaluation.

• Proficient in Reporting skills, like Proc Report, query report, Proc Print, Proc Means, Proc Freq, labels,

formats, titles, footnotes, and other report options.

• Solid MS Excel analysis skills in descriptive statistics, correlation, histogram, moving average, regression,

sampling, probability distribution, time series and modeling.

• Profound knowledge in Relational Databases of Oracle, DB2, SQL Server, MS Access etc.

• Terrific time management skills, optimized work process to complete projects on schedule.

• Demonstrated constructive working relationship, successful interpersonal communication, multitasking and

prioritizing skills, solved problems following company rules and routines.

WORK EXPERIENCE

Data Analyst AZ Financial, Richmond Hill, ON 2009/01 Present

AZ financial company provides products and service include life insurance, medical insurance, tourist insurance,

international student insurance, critical disease insurance, RESP, mutual fund, etc.

Achievements: helped Company to increase sales 21.7% by using RFM model, penetration analysis, profiling,

segmentation, and logistic regression model to predict which customer would accept offer.

Responsibilities:

• Fulfilled project to profile and segment customers, used KPI (age range, gender, province, month, account

combination, channel, tenure, claims) to analysis company’s performance and customer’s pattern.

• Built descriptive response model for campaign to find customer’s response pattern and trend; troubleshooting

when campaign don’t go as expected, used top reasons for further campaign strategy improvement.

• Finished pre-campaign strategy design. Used KPI to segment/profile prospects into groups and executed

specific strategy to different group, applied logistic regression to find high response probability prospects.

• Accomplished post-campaign assessment, used ROI to evaluate the campaign performance.

• Finished insurance project about retention and segmentation by using data step, Proc sql, Macro, Proc report,

Proc gbarline; output report includes html panel, and table integrates with drill down button.

• Finished predictive logistic regression model, used dataset of out-of-time to validate the model, check the

acceptability of model, improved model performance by tuning coefficient.

• Output list report, summary report, table, graph, html file and PDF file for users.

• Completed risk model to find customers with high risk by using logistic regression, used Proc freq, Proc

means, Proc univariate, Proc sort, Macro, Proc logistic to build model, ROC plot to check the model.

• Extracted, transformed and loaded raw data from different source. Apply validation and reconciliation to the

data to ensure accuracy for further analysis.

• Cleansed raw data by using Proc Freq, data step, Proc SQL for character data, using Proc Means, Proc Format,

Proc Univariate, Proc SQL, Data Step for numeric data.

• Built RFM model to identify high value customer group who has high probability of response by using SAS

Proc Freq, Proc Means, Proc Sort and Proc Tabulate.

• Designed a campaign project, it includes cross-sell and up-sell to high value customers.

• Ordered external credit score file from Equifax and read in the data file for analysis.

Senior Analyst Mawan Electric Power Company, Shenzhen, China 2007/01--2008/09

Mawan Electric Power Company is one of top 500 industrial companies in China, its core business includes

electrical power unit construction, manufacturing, environment protection and marketing.

Achievements: Company profit increased 18.6% by helping company to find high value customers; customer

churn rate decreased from 5.39% to 3.86% by using retention model.

59 Milos Road, Richmond Hill, ON Reference available on request

Don Wang 905-***-**** Email:*********@*******.***

Responsibilities:

• Built predictive model by using internal and external data to find profitable customers; check prospect’s

qualification and avoid high risk customers who will bring potential loss to company’s profit.

• Built retention model to predict customers who would voluntary churn. Segment customer by KPI variables

and employ Proc Freq, Proc Print, Proc SQL, Proc Report to generate report.

• Developed descriptive regression models based on a great deal of historical data analysis.

• Met with users to understand and review specific reporting needs, designed analysis process for solution.

• Provided weekly, monthly, quarterly, annually business performance report to management.

• Completed penetration analysis, segment customers and design specific campaign strategy.

• Developed programs to output reports, graph, tables; and prepared explains and presentation to management

and stakeholders; provided them with executable solution.

• Used scoring algorithm to find customers with high risk by setting up risk score; using Proc Logistic to select

variables used in model and applying left chart to validate model.

• Used AIC index to evaluate the quality of model and provided improvement plan.

• Researched on new technology and skills, applied new methodologies to improve team’s productivity.

• Analyzed customer behaviour trends, direct-to-consumer marketing initiatives and campaign results.

• Completed feasibility research and supplied detailed plan to solve business problems.

• Provided sufficient technical training and support to new team members.

Analyst Mawan Electric Power Company, Shenzhen, China 2005/05--2006/12

Achievements: Used profiling/segmentation to find prospects for company, found customers with high risk, kept

constructive working relationship with clients; Performance was highly appreciated by management team.

Responsibilities:

• Attended technical meeting to understood user’s business requirements, verified technical requirements.

• Wrote SAS/SQL and SAS/Macro program and used some advanced programming techniques to boost working

efficiency and ensure to complete projects on schedule.

• Reconciled, validated, modified and combined data by using different SAS procedures such as Proc Format,

Proc Freq, Proc Univariate, Proc Means, Proc SQL, Proc Summary, Set, Merge, etc.

• Completed customers profiling/segmentation, found profitable customers for company.

• Synthesized large amounts of complex data from multiple sources in different formats such as Excel, Access,

delimiter file, text files and database Oracle, DB2, SQL Server, etc.

• Extracted and transformed data from different source like raw data, PC file, DB file, server file, mainframe file;

loaded data into data warehouse for further data analysis.

• Created SAS application like html, PDF, RTF, csv, Access file.

EDUCATION&CERTIFICATE

Bachelor degree in Produce Process Automation, Southeast University, Nanjing, China 1993

SAS Certified Advanced Programmer for SAS9 2013/10

SAS Certified Base Programmer for SAS9 2013/08

59 Milos Road, Richmond Hill, ON Reference available on request

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