Komlan Setodji

adg8b7@r.postjobfree.com

763-***-****

Tampa, FL

Summary:

Data Analyst Consultant/ Data Quality Analyst Consultant/ Business Technical Analyst.

Enjoy working in teams. Strong communication skills.

Hard working, ethical and highly results oriented. Ability to quickly grasp and apply new concepts and technologies.

Education:

Master of Science in Applied Statistics GPA 3.43

University of Delaware, Fall 2019

Bachelor of Science in Statistics GPA 2.91

School of Statistics, University of Minnesota-Twin Cities, Minneapolis MN Fall 2013

North Hennepin Community College, Brooklyn Park, MN GPA 3.29

Related Coursework: Data Analysis, Applied Linear Regression, Design and Analysis of Experiment, Theory of Statistics I & II, Applied Multivariate Methods, Senior Project, Bio statistical Methods I, Intro to SAS Programming, SAS Procedures and Data Analysis, Applied Research Methods, Survival Analysis, Logistic regression.

Certification:

SAS Base Programming for SAS 9

Academic Experience:

Project: Developed a multinomial logistic regression model to understand obesity issue among US children between the age 3 and 5 years and to discover some of the factors that impacts them to be obese or not. (Master’s thesis), Fall 2019

Pulled data from observational survey study designed by NHANES (National Health and Nutrition Examination Survey) to discover three essential factors that are the body mass index, the age of the child at the time of the examination, and the gender of the child.

Developed three different multinomial logistic regression models: response variable is a categorical variable and has 4 levels, underweight, normal weight, overweight, and obese.

Resulted in conclusion that in the third model for instance the odds of the body mass of a child to be overweight is 0.012 times as large as the odds of the body mass of the child to be obese.

Used SAS for analysis.

Project: Developed a completely randomized design (CRD) study to understand how the duration of time spent by an athlete reflects on the calories burnt during physical activity excercises, Fall 2018

Collected data during jogging by using a watch

Collected one numeric dependent variable: calories_burnt

Collected two independent categorical variables: time which is an indicator factor 1 (time >= 60 min) or 2 (time <= 48 min), and hours for morning, or evening

Resulted in conclusion that for the athlete to burn more calories, he will have to consider running for every unit of the time to be able to burn in average 120 units calories.

Project: Developed a one-sample proportion research to investigate whether the decision made by the federal government reflects the opinion expressed by the protestations on twitter about the North Dakota Pipeline, Fall 2016

Used Python to collect about 203,692 tweets, and exported into R.

Used one-sample proportion statistical analysis to measure the responses expressed in the tweets through the use of hypothesis tests.

Resulted in conclusion a large majority of the population of twitters who twitted about this topic is in disagreement with the federal government’s decision and tweets that are against the construction of the pipeline are instead reflected by the federal government’s decision.

Project: Developed a time series model to predict the number of expected patients in upcoming years, Fall 2015

Used excel functions to clean metrics and exported into R. Developed the appropriate model for the client (Clinic) to predict the expected number of patients in the upcoming years in order to make sure that an adequate number of doctors is available to respond to the demand, and hence to avoid fines from health administration organization, and to mitigate a higher cost incurred due to exterior clinic hired to fulfill patients’ demand.

Project: Investigation about the implementation of the smoke-free and tobacco-free policies at the University of Minnesota, Fall 2013

Conducted a cross-sectional design to investigate and understand undergraduate student’s perceptions towards the University of Minnesota comprehensive campus smoke-free and tobacco-free policies, and their difficulty to access some areas on campus due to exposure to secondhand smoke.

Software STATA was used to discover that non-smokers and non-tobacco products users supported the policies while they did not show any interest of avoiding educational or recreational events on campus for fear of being exposed to secondhand smoke.

Project: Pay less or more: Students’ behavior toward textbook prices (Senior Project), Spring 2013

Conducted an original survey on campus of University of Minnesota, to determine how much students are willing to pay for a science textbook assuming that it is needed for a class, with students randomly chosen from a group of participants, where the ordinary linear regression was used with R statistics, and concluded that female are reluctant to spend more money than male students while the cost offered for a particular book is determined by both the gender, and the status (used or new) of book.

Project: Soma population, Sprint 2013

Conducted a multivariate data analysis on a Soma population by pulling out data from R database, and by using MANOVA PROC GLM to test and see whether there is a difference between boys and girls of 2 years of age in terms of their weight and Height.

Prior to that, PROC UNIVARIATE was used to check the normality assumption, PROC DISCRIM was used to check the homogeneity of the variance-covariance matrix, and PROC GLM was used to check the diagnostic plots. In addition PROC GLM was used to predict the gender from a new dataset based on a previous GLM model developed from the original dataset.

In R, Classification tree, stepwise selection, ridge regression, LASSO, and PCA (Principal Component Analysis) were used to select variables, and identify the model with the best mean square error.

In R, Naïve Bayes is used to predict the value of gender from a test data by using the best model.

Project: Effects of Chemical Products on Laundry, Fall 2012

Designed, and analyzed a Randomized Complete Block (RCB) design about the effects of chemical products on laundry by choosing the right design, collecting data, analyzing, and concluding on the findings that revealed the best chemical product among all the others.

The statistical package used was R.

Skills:

Programming Languages: C++, JAVA, R, Python, Pig, Hive, Mapreduce, Hadoop, Stata, SQL, JMP

Software/Databases: Excel, PowerPoint, and Microsoft Word, TOAD, GitHub, Teradata, Oracle, MySQL

Operating Systems: Windows, Linux, Citrix, UNIX

Software: Excel, PowerPoint, and Microsoft Word, TOAD, GitHub

Operating Systems: Windows, Linux, Citrix

Database: Teradata, Oracle, MySQL

SAS Tools: SAS/BASE, SAS/GRAPH, SAS/STAT, SAS/MACROS, SAS/SQL, SAS/INSIGHT, SAS/ARRAYS SAS ENTERPRISE MINER 12.1 & 13.2

Languages: French & English

Work Experience:

Reason of Employment Gap: Doing Masters

WellCare, Tampa, FL Aug 2018 – Oct 2018

Business Technical Analyst

Used SAS (EG & SAS Studio), SQL, and UNIX to create technical file from a flat file according to the requests of the mapping.

Used WINSCP to transfer flat files between Windows and UNIX.

Used EMR, Electronic Medical Record, flat file in SAS to create an output file that is appended into the SQL server and delivered to the client.

Performed joints between columns either with SAS data step or with PROC SQL in order to find the generic code and the provider specialty attributed to each member identification.

Closed a care gap in the final output record for each member by effectively assigning to the member identification a generic code.

Transform CPT codes of member from multiple columns into a unique CPT column corresponding to many rows for the same member.

Used the DO LOOP in SAS to transform the BP, blood pressure measurements, of members, initially stored onto a unique row by creating duplicate rows for each member to store the BP measurements.

Used the data step in SAS to assign a BMI, body mass index, to a member based on the BMI measurement of the member.

Reason of employment gap: Was in school

Wells Fargo, Minneapolis, MN Aug 2015 – Jul 2016

Security Operation Specialist Consultant

Handled different types of transactions such as shares, money, and currency exchange, foreign exchange (FX).

Called to book and confirm the rate of a deal.

Administered the database to balance all the transactions and operations of the day.

Used Mainframe (banking financial interface) to process transactions.

Target Corporation, Minneapolis, MN Nov 2014 – Feb 2015

Data Quality Analyst Consultant

Wrote SQL queries on Teradata and Oracle to perform data validation.

Used SAS to perform analysis on the data by comparing data from both Teradata and Oracle.

Wrote test cases by using SQL to check the migration of the data from the landing through the staging, and into the foundation table.

Wrote test cases to check business rules.

Wrote test cases by using SQL to check the availability of the data in each table.

Stefanini, Davenport, IA Jul 2014 – Oct 2014

Data Analyst Consultant

Performed data analysis on merchants’ locations by using SQL queries in TOAD ORACLE database.

Used SQL queries on UNIX by logging into Netezza.

Used Excel to write rules to remove and add merchants’ location from an aggregate.

Contact this candidate