Data Management
Resume:
Xinxin
Wang
************@*****.***
EDUCATION
The
University
of
Texas
at
Dallas
December
**** *.*.,
Business
Analytics- Management
Science
and
Quantitative
Methods Changzhou
Institute
of
Technology
June
2014 B.S.,
Business
Administration
BUSINESS
EXPERIENCE
Hangzhou
Aupu
kitchen
Technology
Co
Ltd,
Hangzhou,
Zhejiang,
China Data
Management
–
Marketing
Activities
on
E- Commerce
June
2014
–
June
2015
• Built
database
system
of
5000+
sales
data
customer’s
data,
vendor’s
data
using
SQL
based
on
relational database
schema
and
presented
well- received
results
with
$10,000
potential
savings
in
data
management
• Developed
regression,
logistics
regression,
cluster
analysis
based
on
demographic
attributes
and
behavior attributes
to
identify
the
class
of
customer
using
SAS
• Designed
marketing
strategies
for
over
3
marketing
activities
by
EXCEL
SOLVER,
vlookup,
pivot
table
and SPREADSHEET
and
promoted
the
revenue
from
$200,000
to
more
than
$1,000,000 ACADEMIC
PROJECT
Database
Marketing
January
2016
–
May
2016
• Identified
the
low
value
customers/cherry
pickers
from
2000
observations
and
divided
data
into
80%
test
data and
20%
validation
data
to
improve
coupon
promotion
campaign
using
SAS
• Performed
clustering
analysis
with
result
of
1016
high
value
customers
and
984
low
value
customers,
logistic regression
with
85.2%
percent
concordant
and
recommendation Applied
Econometrics
August
2016
–
December
2016
• Estimated
the
regression
model,
fully
interpreted
multicollinearity
by
VIF
with
the
value
more
than
10
• Tested
significant
factors
due
to
p- values
smaller
than
0.05.
Identified
171th
observation
with
high
per
hour wage
and
200th
observation
with
low
per
hour
wage
and
dropped
them
with
INFLUENCEINDECPLOT
by
R
• Modeled
the
time
series
model
and
tested
whether
the
average
temperature
is
significantly
increasing
(one- sided
test)
over
the
decade
due
to
rejection
of
hypothesis
with
0.243
p- value Database
Foundations
August
2016
–
December
2016
• Built
and
optimized
database
system
for
Shanghai
M&G
Stationery
Inc
to
make
information
being
more efficient
with
SQL
by
Microsoft
Access
and
helped
to
save
cost
by
10%
after
implementing
• Dragged
out
columns
and
rebuild
them
into
7
new
tables,
built
relations
among
customer
info,
shipping methods,
profit
records
and
order
records
due
to
relational
database
schema
and
functional
dependencies Big
Data
Analytics
January
2017
–
May
2017
• Analyzed
the
provided
financial
attributes
to
create
predictive
models
of
the
probability
in
prospect companies
being
bankrupt
or
non- bankrupt
• Deployed
Hive
to
split
data
into
1
testing
data
and
3
training
data
for
validation
purpose.
Explored
decision tree
2
with
the
lowest
ASE(0.097)
and
logistic
regression
with
ROC(0.77)
curve
• Compared
estimation
results
with
the
actual
values
of
bank
status
in
all
observations
in
the
testing,
training1, training2
and
training3
datasets.
CERTIFICATIONS/LICENCES:
SAS- UT
Dallas
Data
Mining
and
BI
July
2017 TECHNIQUE
SKILL:
Business
Intelligence,
Relational
Database
Management,
Spreadsheets,
Data
Mining, Warehousing,
Programming,
Microsoft
office,
Microsoft
Access,
Hadoop,
Hive,
Pig,
SAP,
ERP LANGUAGE:
Python,
SQL,
SAS,
SAP,
R,
SPSS,
Java,
STATA COURSEWORK:
Prescriptive
Analytics,
Business
Intelligence
Software
and
Techniques,
Database
Foundations, Advanced
Business
Analytics
with
SAS,
Big
Data
Analytics
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