SUMMARY

• Highly experienced in data science application projects, visualization, presentation, and documentation skills.
• Highly methodical, performance - focused, and results-driven professional with extensive experience in data analysis and environmental technology within IT field.
• Equipped with expertise in industrial research, project management, predictive analytics and modeling.
• Skilled at identifying process optimization strategies and cost-effective initiatives toward revenue growth.
• Known as a proactive team player with proven ability to cultivate and maintain long-term relationships with diverse individuals of all levels.
• Experienced in working at different domains; such as, higher education and research institutes, manufacturing and engineering companies. Passionate about teaching, researching and data analysis.
• A very good knowledge and experience in R, Excel, Web scraping, SQL, SSIS and data visualization.
• Excellent ability in identifying data requirements for analysis, data cleaning, wrangling and modeling
• Comfortable with handling both structured and unstructured data, exploratory data analysis and very familiar with supervised and unsupervised machine learning algorithms, time series and survival analysis methods.
• Excellent team building, organizational, interpersonal, written and oral communication and reporting skills.
• Immense ability to effectively work and learn in a diverse and multi-cultural environment.
• Worked with senior management to create HR policies and procedures; recruit employees; create group benefits databases, and develop orientation and incentive programs.

TECHNICAL SKILLS

Statistical and programming Tools: R, SQL, SAS, ETL/SSIS, Python, Advanced Excel (Pivot Tables, VLOOKUPs)

Big Data: AWS (EMR, EC2), Spark, Data Lake, Impala

Statistical Analysis: Descriptive statistics, Hypothesis testing, Design of Experiments, Exploratory data analysis

Predictive Modeling and Machine Learning: regression, classification and clustering techniques; such, as linear and logistic regression, shrinkage methods (Ridge, Lasso, Elastic Net), Decision Trees, Random forest, SVM, NN, Naïve Bayesian, PCA, time-series and survival analysis and text mining.

Data Visualization and Reporting Tools: Tableau, ggplot2 (R), R-Markdown, R-Shiny, Plotly

PROFESSIONAL EXPERIENCE

Confidential - Morrisville, NC

BI/Tableau Developer and Data Scientist

Responsibilities:

• Implement various data analysis and visualization techniques. Design and implement data solutions via Tableau Dashboards and analytical models which help infrastructure and application developer teams to mitigate risks associated with capacity management of the IT infrastructure.
• Develop predictive models for forecasting future IT infrastructure demands, need for expansions or decommission. Extensively used Excel, SQL, Tableau, and R for data analysis and modeling.
• Migrate existing complex Dynamics Excel dashboards in to Tableau and create interactive intelligent Dashboards in Tableau
• Create reports and KPIs detailing the finding from the Analysis and present the result to decision makers
• Deliver proactive capacity management capability across all aspects of IT infrastructure to ensure the capacity of IT services meets the evolving demand of the business in a cost effective and timely manner

Confidential —Washington, DC

Data Science Course Content Creator

Responsibilities:

• Extracted and cleaned data from various sources and build predictive models using R and Python
• Built predictive models by using train and test data. And calculate predictions accuracies, and compare the predictive power of models based on their error rate.
• Prepared training materials and give training on data science for corporate clients
• Classified documents for federal clients using text mining and SVM machine learning algorithms and automate the manual document classification process. Hence, reduced time and cost by more than 50%.
• Created data visualizations and built interactive dashboards using R-Shiny and plotly and ggplot2

Confidential — Concord, New Hampshire

Student Data Analyst Consultant

Responsibilities:

• Extracted, transformed and loaded data of more than 10,000 undergraduate students from different data source using ETL process and integrated with SQL server using SSIS. Cleaned, merged, analyzed, and modeled data.
• Wrote SQL quarries and manipulated the data, created views, triggers and stored procedures.
• Created 5 homogeneous groups of students using K-Means and Gower clustering unsupervised Machine Learning algorithms in R and identified students who are at a higher risk to dropout and require immediate intervention.
• Built predictive models using R, Python and SAS. Developed classification models using Random Forest, SVM and Logistic regression machine learning algorithms to predict whether a student will graduate. Train, test and validate the models and compared their predictive power based off their accuracy and misclassification error rates.
• Applied Survival Analysis and Cox Proportional Hazard Rate Modeling using SAS and determined the relevant weight of factors which determine students’ academic success at Confidential .
• Developed and maintained advanced reporting, analytics, dashboards and other BI solutions using Tableau and provided Tableau support to users
• Examined association of various factors leading to students’ dropout at Confidential where discovering of pattern or association helped in effective decision making and intervention.
• Created visualizations, reports, dashboards and stories on Tableau and presented the findings to the higher-level managers at Confidential
• Developed interactive dashboards and documented standards and best practices for development, administration and use of the Tableau platform/applications
• Performed data joining and blending, created calculated fields, time-series analysis, aggregation, filters, Maps, scatter plots, Dual Axis charts, built interactive dashboards, and storytelling using Tableau.

Confidential — Durham, North Carolina

Data Analyst/Tableau Developer

Responsibilities:

• Analyzed historical data using SAS, SQL, R and excel to determine the factors of a semiconductor device failure and derived insights to develop best process practices
• Extracted data using SQL and formulated visualization techniques using Microsoft Excel and JMP and Tableau for the identification of data relationships, trends, and anomalies
• Monitored and adjusted semiconductor production process and equipment for improving quality and productivity
• Determined root cause of system deficiencies which caused product defect, scrape and equipment failure and communicated the findings to the design engineer to facilitate effective corrections
• Conducted correlation analysis between different parameters within the existing and past operations, and integrated findings for process modification and better yield
• Provided technical support in developing, building and testing prototypes, new products, processes, and procedures, and gave training and advice to other technicians and operators.
• Developed statistical models, algorithms, SQL quarries, and methodologies to classify, predict, and quantify performance metrics, anomalies, defects, and faults in process data
• Designed and implemented proof of concept solutions and created advanced BI visualizations using Tableau.
• Established interactive intelligent dashboards with real-time indicators of manufacturing floor conditions, wafer reworks, and scrapes as percentage of revenue, equipment and process health, enabling managers to achieve faster and more precise decisions by 65%
• Deployed monitoring control charts and executed root cause analysis for detecting defects using historical data, and failure analysis to determine the factors of a semiconductor device failure to control and optimize processes within specified limits
• Leveraged different data architectures and data blending technologies to provide data to Tableau and built dashboards to provide insights
• Created and managed Tableau sites, projects and workbooks, groups, data views, data sources and data connections
• Performed maintenance and scheduling of Tableau Data Extracts using Tableau Server and the Tableau Command Utility. Publish results and dashboards on Tableau server
• Made significant contribution in saving over $40K in annual sales through creation of customer profiles to identify key groups of customers and mechanisms for increasing sales

Confidential

Data Analyst/BI Developer

Responsibilities:

• Participated in Requirement gathering, Business Analysis, User meetings with both onshore and offshore team, discussing the issues to be resolved and translating user inputs into ETL design documents along with capturing specific data and analysis of the root cause of problem.
• Worked on the Data Warehouse team analyzing data files that had to be compiled from disparate non-production sources and readied them for production. Tasks included: comparing data to requirements documentation, creation of data layouts, data dictionary, and the pipe delimited and fixed width files.
• Participated as member of a project team performing various lifecycle tasks for an intranet application with SQL Server 2008 database.
• Worked on Source fields to Target fields mapping and put the transformation rules for each field.
• Delivered global equities and derivatives regulatory compliance related solutions across multiple clients.
• Created the data definition in Excel for each field for all source systems which came out from different Database Engines.
• Integrated, analyzed and reported financial information using SSIS, SSAS, SSRS
• Worked with data mining, data cleansing, data modeling, data manipulation, record matching, table linking, table structures, importing and exporting.
• Created Source Mapping Excel Sheet for our group where all source and target fields are mapped and all business rules are applied to map all fields. Also worked on Intercompany Transaction activity for reconciliation process.
• Created SQL complex queries and SQL performance tuning.
• Team Building, creating production and analysis report, documentation for various data processes.
• Good experience in communicating with different source persons, scheduling meeting with Source Business Person as well as Source Technical Persons.
• Created final source approval and Gap/Recommendation Technical Document for each source systems.
• Designed some Source system related diagrams using Microsoft Visio and prepared presentation on that.
• Prepared documented reports for the usage of existing systems and new systems.

Confidential

Researcher and Lecturer

Responsibilities:

• Held responsibility for the collection, analysis, and modeling of over 100,000 student data records from 30 universities in Ethiopia through methods, such as linear and logistic regression using SPSS
• Conceptualized graphical and numerical summaries of data and presented findings to a nonmathematical audience
• Examined and interpreted data collected from field research by coding qualitative data and performing statistical tests
• Imparted knowledge to senior and junior undergraduate students regarding courses on environmental technology and resources management and statistics
• Gathered data and performed statistical analysis, while writing reports and presenting findings to stakeholders
• Designed an algorithm using probabilistic models to predict user's admissions chances in college and university based on standardized test scores and high school grade point average (GPA)
• Demonstrated expertise in statistical analysis and probabilistic models for the prediction of successfully finding a job by major, degree-level, and university and college