Data Analyst Scientist
Resume:
Genet Sebehat L
Data Analyst
Work Experience
Epsilon, March 2023-Present
Data Analyst/Data Scientist
Utilized the Waterfall methodology of development for Requirements, Planning, Design, and Deployment.
Worked on data cleaning and ensure data quality, consistency, and integrity using NumPy, SciPy, and Pandas.
Create interactive visual dashboards using Power BI and Tableau
Worked in using collections in Python for manipulating and looping through different user-defined objects.
Proficient with Python 3.x including NumPy, Scikit-learn, NLP, Pandas, Matplotlib and Seaborn.
Ability to write and optimize diverse SQL queries, working knowledge of RDBMS like SQL Server and MySQL.
Data validation and cleansing of staged input records was performed before loading into Data Warehouse.
Holding a knowledge working with Source Tree with GitHub.
Planned System International, March 2022–Feb 2023
Data Scientist
Create interactive visual dashboards using Power BI and Dax formula to migrate CATS system to E2 with 98.3% accuracy and updated/modified dashboards based on Q&P team feedback.
Successfully changed the old system logic (Crystal report logic) to a new system logic based on the business requirements, using Power BI Dax logic/queries that reduced data errors by 13% and improved data processing speed by 29%.
Develop and maintain the programs in SQL Server Integration Services and T SQL.
Maintain ETL and refreshed combined data set on a daily basis, achieving 97.3% uptime for combined dataset refreshes.
Seek out a broad understanding of our customer’s technology platform and products and align design efforts with that context.
CDC Foundation, Feb 2022-Apr 2022
Data Analyst
Full life cycle activities of data analytics to include requirements and design, data cleaning, developing analysis and reporting capabilities, linking databases and data sets.
Continuously monitoring performance and quality control plans to identify improvements in models; and to do related work as required, increasing model accuracy by 12% and reducing model execution time by 18%.
Perform basic data management, data cleaning and statistical analysis using SAS, R, or other statistical programming language on COVID-19 data to complete data extracts.
Produce and analyze reports for the purposes of monitoring disease trends and providing timely data in support of COVID-19 response and to inform the public.
Janveesoft, Client- Unum & Hartford Financial Service group Aug 2018-Feb 2022
Junior Level Data Scientist
Successfully implemented Agile/Scrum Methodology for reporting project life cycles, resulting in improved project efficiency and reduced development time by 29%.
Effectively managed sensitive client data and ensured data standardization and formatting using Microsoft Excel and R prior to importing to centralized databases, minimizing data errors and improving data quality by 83%.
Applied Machine Learning Classification Algorithms like Logistic Regression, K-NN, SVM, Kernel SVM, Naïve Bayes, Decision Tree and Random Forest classification to solve complex business problems and achieve improved decision-making.
Successfully implemented requirements using SSIS, T-SQL, and SSMS, ensuring seamless data integration and automation.
Utilized Tableau, and QlikView for Ad-Hoc reporting, enabling data visualization and exploration.
Demonstrated outstanding pre-eminence in Data extraction, Data cleaning, Data Loading, Statistical Data Analysis,
Exploratory Data Analysis, Data Wrangling, Predictive Modelling using R and Python.
Soliditary Movement for New Ethipia (SMNE), Jul 2017-Ju1 2018
Data Analyst
Optimized T-SQL Code: Employed advanced T-SQL techniques including subqueries, functions, and aggregate functions such as MAX, MIN, and COUNT, resulting in a significant 29% reduction in query execution time. Additionally, enhanced query readability and maintainability for future development and troubleshooting.
Database Design and Schema Improvement: Crafted databases and schemas tailored to optimize performance, contributing to a notable 13% enhancement in overall database efficiency. Implemented strategic indexing and normalization strategies to streamline data retrieval and storage processes.
On-Demand Reporting System Enhancement: Developed a sophisticated on-demand reporting system capable of generating customized reports and automatically dispatching them via email. This initiative led to a substantial 22% increase in report utilization, empowering stakeholders with timely insights and facilitating data-driven decision-making.
Performance Optimization and Troubleshooting: Proactively enhanced existing queries by identifying and resolving over 53 performance bottlenecks. Utilized comprehensive profiling and diagnostic tools to pinpoint inefficiencies, implementing targeted solutions to enhance query performance and overall system responsiveness.
These accomplishments demonstrate a comprehensive approach to database management, encompassing both strategic design considerations and tactical optimizations aimed at maximizing operational efficiency and user satisfaction.
Metropolitan State University, Denver, Colorado Nov 2012 – Jun 2017
Assistant Director of Data Management/Senior Data Analyst.
Performed different kinds of reports (daily, weekly, monthly, quarterly, and yearly report) based on the requirements and provided data that assisted with development of all admissions recruiting and outreach efforts, reduced report generation time by 49% and increased data accuracy by 93% as a result.
Developed campaigns using Banner Relationship Management (BRM): Created Business Rules. Created templates and attached with BRM email contents based on business requirements. Created constants that efined pieces of information within a rule for those values we do not want to change. Created different population lists based on the BRM campaign requirements. Monitored BRM communication log emails and alert checks.
Enhanced and automated existing reports using different tools to provide requested data or reporting information for the Office of Admissions and other University offices that streamlined data collection and reporting processes, reduced manual report generation by 69% and improved report accuracy and timeliness.
Performed unit and system testing to ensure data integrity, ensured accurate data-driven decision-making.
Developed user-friendly and informative web pages to enhance the admissions experience.
Cleansed Row Data for Not On file (NOF) and created Excel reports for the Admissions processing team that streamlined data processing for admissions staff.
Uploaded and processed TAP load exams (ACT, GMAT, and SAT). Efficiently processed and integrated external exam data into the student information system and maintained accurate and up-to-date student records.
Experienced with student information systems, i.e., Banner.
Location: Aurora, Colorado
Mobile: +1-612-***-****
Email id: *************@*****.***
Certifications
Microsoft Certified Technology Specialist (MCTS) in SQL Server 2008 Database Development
New Horizons, Englewood, CO
MCTS in SQL Server 2008 Implementation and Maintenance
New Horizons, Englewood, CO
Oracle Database 11g Administrator Certified Associate (OAC)
Private, Denver, CO
People Tools Development Certified Expert
Private, Minneapolis, MN
Skills
Languages: Python, R, JavaScript, html
Technology: ETL, Reporting, Data Mining, Data Analytics, Data warehousing, Big Data, Statistics
Tools: Cognos, Tableau, Jupiter, R studio, Power BI, Excel
Databases: Oracle, SQL Server, PSQL, MY SQL, PostgreSQL
Library: Pandas, NumPy, Matplotlib, TensorFlow, PyTorch, Plotly
Operating Systems: Microsoft Windows, Linux, MacOS
Methodologies: Waterfall, SDLC, SCRUM, Agile
Training
SQL Server developer 2016, SSRS SSIS, EECD MSFT, 2017, Denver, CO
Customization and Configuration in Microsoft Dynamics CRM, 2015, MSU, Denver, CO
Report Studio Developer Training - Part 2 IBM Cognos, 2014, MSU, Denver, CO
Report Studio Developer Training - Part 1 IBM Cognos, 2014, MSU, Denver, CO
TSQL SQL Server 2008 Database Development SQL Server 2008 Implementation and Maintenance, New
Horizons, Oct 2010 – Sep 2011, Englewood, CO
People Tools I/ People Tools II Accelerated Release 8, Oracle University, 2007 MPLS, MN
People Code Rel 8.44 ED1, Oracle University, 2007, Minneapolis, MN
Quality Assurance Testing, 2005, Accenture, Atlanta, GA
Education
Master of Science in Data Science 4.0 GPA, Regis University, Dever, CO, USA
Bachelor of Science Degree in Computer Information System, Minnesota State University, Mankato,
Summary
Over 10+ years of experience as a Data Professional, specializing in Data Analysis for 7+ years.
Skilled in developing and implementing data-driven solutions to improve decision-making, enhance operational efficiency, and drive business growth.
Successfully enhanced and automated existing reports using different tools for the Office of Admissions and various University offices.
Streamlined data collection and reporting processes, reducing manual report generation by 69% and improving report accuracy and timeliness.
Extensive experience in Excel for large datasets, with proficiency in Power BI and Tableau for interactive reporting.
Proficient in SQL and MS BI Suite for ETL (Extract, Transform, Load) and reporting solutions.
Experienced in Data Mining, Statistical Analysis, Data Engineering, Software Development Life Cycle (SDLC), Agile, and Waterfall methodologies.
Skilled in Data Visualization and proficient in Python and R programming languages.
Possess comprehensive skillset encompassing data acquisition, cleaning, transformation, modeling, and visualization across diverse industries. Leverage machine learning techniques to extract valuable insights and drive impactful decision-making.
Familiar with design, management, and query of databases using Access, SQL Server, Oracle, PostgreSQL, and MySQL databases.
Demonstrated proficiency in Statistical Machine Learning techniques, leveraging advanced algorithms to derive insights and predictions from complex datasets.
Experienced in the Agile and Waterfall methodologies, adept at adapting to different project management approaches to meet project requirements and timelines effectively.
Skilled in Data Engineering tasks, including designing and optimizing databases, creating data pipelines, and ensuring data quality and integrity.
Possess a strong foundation in machine learning algorithms encompassing supervised (linear regression, decision trees, random forests, etc.) and unsupervised learning (k-means clustering, etc.) techniques for classification, regression, and pattern recognition
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