240-***-**** ad3of5@r.postjobfree.com

Experienced and results-oriented Senior Data Scientist with a proven track record of leadership, I am actively seeking opportunities to apply my expertise as a Senior Data Scientist or Project Lead. Currently pursuing a Ph.D. in Computational Sciences and Informatics, I bring a solid foundation with a master's degree in science and a bachelor's degree in information system management. My credentials include a diverse set of certifications such as CompTIA Security+, Advanced Machine Learning in Python, Time Series Analysis and Forecasting, as well as AWS Machine Learning with Sagemaker and AWS Architect Associate.

Dedicated to leveraging data for informed business decisions and process optimization, I am enthusiastic about contributing my analytical and scientist skills and managerial experience to a challenging new role.

Advanced Data Analysis: Proficient in extracting insights from large and complex datasets using statistical analysis and machine learning techniques.

Predictive Modeling & Analytics: Skilled in developing predictive models and conducting exploratory analysis to inform strategic decision-making.

Data Visualization: Proficient in using tools such as Tableau and Power BI to create dynamic, interactive dashboards and reports that effectively communicate data insights.

Machine Learning Techniques: Comprehensive understanding of modern machine learning techniques including classification, clustering, regression, deep learning, and NLP.

Core Competencies

Data Analysis

Predictive Modeling

Data Visualization

Machine Learning

Cloud Technologies

Big Data

Agile Methodologies

Stakeholder Communication

Problem Solving

Continuous Learning

Statistical Proficiency

Team Leadership

Professional Experience

SR DATA SCIENTIST 09/2019 to 11/2023

Accenture Federal Services, Mclean, VA

Championed data operations, facilitating the development and integration of Machine Learning (ML) and Artificial Intelligence (AI) algorithms for test-driven development and operational enhancement.

Forged collaborative relationships with software engineers, data engineers, stakeholders, business process leaders, and architects, leading data extraction, transformation, and standardization initiatives to optimally prepare raw data for ML and Business Intelligence (BI) environments.

Executed and documented complex, evolving requirements in an agile environment, liaising effectively with program management and engineering teams to ensure seamless progress and adaptation.

Provided comprehensive analytics, insights, reports, and strategic recommendations to the executive leadership team, driving informed decision-making across all business units, distribution channels, and product lines.

Engineered a range of ML algorithms, including Classification, K-means clustering, DBSCAN clustering, NLP model, and multivariable analysis, resulting in the detection of spam emails, identification of correlations among survey questionnaires, and determination of unknown responses handling for better subject state understanding.

Developed a dynamic Power BI dashboard for real-time data visualization, offering various forms and filters, thereby enabling the executive committee to perceive data trends effectively and make informed decisions.

Orchestrated the development of sophisticated algorithms based on comprehensive statistical analysis and predictive data modeling, bolstering the optimization of business processes.

Utilized Python libraries such as Requests, Dataclasses, Beautiful Soup, Selenium, and other tools for comprehensive web scraping.

Developed a configuration scraping pipeline using Python to enhance data processing efficiency.

Conducted Social Network Analysis employing Python libraries like Igraph, Networkx, AdjustText, among others.

Employed Artificial Neural Network (ANN) for the classification of selectors within a social network, utilizing Python for effective document return.

Integrated data storage with Databricks, leveraging APIs and Python to extract data and construct machine learning algorithms.

Demonstrated expertise in handling complex data cleaning, prediction, and time series forecasting tasks while utilizing advanced querying, visualization, and analytics tools for complex data set analysis and process enhancement.

TEAM MANAGER / DATA SCIENTIST (DISA) 02/2019 to 07/2019

Foxhole Technology: Federal Government Client, Silver Spring, Maryland

Directed a high-performing data science team, spearheading the research and development of the Domain Generation Algorithm (DGA) Correlator and Generator to identify previously unknown malware threats.

Championed client-centric data analysis, utilizing advanced data mining, cleaning, exploration, feature engineering, predictive modeling, and visualization techniques to derive valuable insights from client data.

Conducted rigorous network and security data analysis for clients, leveraging research methodologies to reveal key trends and insights.

Exhibited proficiency in various contemporary machine learning techniques using Python, encompassing deep learning, Natural Language Processing (NLP), clustering, classification, regression, and neural networks.

Demonstrated advanced expertise in extracting insights from intricate structured and unstructured data, adept at identifying patterns, and conducting feature engineering using Python.

Proficient in designing, implementing, and deploying data science products on the AWS Cloud platform, leveraging a sound understanding of data engineering and big data principles.

Adopted Agile/Scrum methodologies to manage project workflows effectively, demonstrating adaptability and efficiency in the fast-paced technology space.

DATA SCIENTIST 12/2017 to 11/2018

RT2 Real -time, LLC, Crystal City, VA

Spearheaded the identification of trends and patterns across extensive enterprise datasets, developing solutions to aggregate disparate data types and formats, and creating predictive models based on stakeholder recommendations.

Executed exploratory data analysis on large datasets using Tableau, unearthing significant trends and patterns, and communicating insights across the enterprise.

Designed an interactive Tableau dashboard to facilitate data-driven analysis, presenting the output as a compelling narrative to engage stakeholders effectively.

Engineered a classification model utilizing Random Forest algorithms to classify data as per stakeholder recommendations, evaluated the model's accuracy, visualized decision regions, and presented findings to stakeholders.

Employed Python libraries to identify and rectify missing data in the dataset, conducted comprehensive exploratory analysis on the acquired data, and communicated findings effectively to stakeholders. The insights provided valuable guidance for strategic decision-making.

Used Python to expertly partition the dataset into training and validation sets, applying machine learning algorithms, including linear regression models, to forecast population counts in multiple countries for 2020. This showcased adept analytical and predictive capabilities.

Assessed various regression models, such as Multi Linear, SVR, and Random Forest, and determined the Multi Linear Regression model as the most optimal for performance using Python. This highlighted a deep understanding of statistical modeling and the ability to choose the most appropriate methodologies for precise outcomes.

PRINCIPAL TEST DATA MANAGER - IBM: Federal Government Client, Washington DC 01/2010 to 03/2018

Principal Test Engineer, 2015 - 2017

Data Migration Lead, 2013 - 2015

Sr. Backend Tester, 2010 - 2013

Sr. Tester, 2009 - 2010

IBM 11/2015 to 8/2017

ANALYTIC AND MODELING ASSOCIATE MANAGER

Utilized analytical tools such as SPSS, SQL, Python, R, and Tableau to supervise Machine Learning and Data Visualization initiatives, implementing comprehensive analysis, reports, and presentations, supporting key business decisions.

Managed the extraction of economic and demographic data from various sources, parsing into predefined structures and overseeing the content deposition into a data sink for secure storage and future use, ensuring data integrity and consistency.

Identified and addressed missing data in the dataset using Python libraries, performed meticulous exploratory analysis on the extracted data, and communicated findings effectively to stakeholders, contributing valuable insights to inform strategic directions.

Skillfully subdivided the dataset into training and validation sets, incorporated machine learning algorithms such as linear regression models to predict population counts in several countries for 2020, showcasing strong analytical and predictive capabilities.

Evaluated various regression models including Multi Linear, SVR, and Random Forest, successfully identifying and implementing the Multi Linear Regression model as the most optimal for performance using python, demonstrating a keen understanding of statistical modeling and an ability to apply the best methodologies for precise outcomes.

IBM 2010 to 2015

PRINCIPAL TEST ENGINEER

Supported four distinct projects across various Government agencies, leading automation strategy formulation for all system requirements, managing project requirements, traceability, and artifacts using VSS, Share Point, Clear Quest, and ensuring progress tracking through completion.

Coached junior testers in Agile principles for sprint-related testing and acted as a core team member in establishing and measuring Quality Assurance methodologies and practices with project teams, focusing on custom test tools.

Designed and implemented detailed test plans, encompassing functional, integration, end-to-end, usability, security, and smoke testing. Developed scenarios, wrote test cases, performed back-end integration testing through SQL queries, and coordinated with developers for defect management and retesting.

Utilized tools such as HP-ALM, ACTS, and VSS for automation, created a robust automation suite for regression testing using HP, and conducted 508 compliance testing, ensuring seamless integration with various platforms and tools.

Spearheaded the Data Integration and Migration Team, fostering collaboration and ensuring that all efforts aligned with organizational goals and compliance standards, resulting in successful project outcomes.

Additional Experience

QA SOFTWARE ENGINEER LEAD - DISC Inc., Washington DC, 09/2005 - 11/2009

Education

Ph.D. Computational Sciences and Informatics, George Mason University, Fairfax, VA, Expected 12/2024

Master of Science Decision Analytics, Virginia Commonwealth University, Richmond, VA

Bachelor of Science Information System Management, University Of Maryland

Computer Programing Diplomat, West Africa Computer Science Institute (Accra – Ghana)

Certification

CompTIA Security + Certified

Machine Learning Advanced Certification Training (Udemy)

Time Series Analysis and Forecasting in R (UDEMY)

AWS Machine Learning (AWS certificate)

AWS Architect Associate (AWS certificate)

Technical Skills

Statistical analysis and modeling

Data and Quantitative Analysis

Data Visualization and Building Dashboard with Tableau and Power BI

Database design, data modeling and advanced queries

Predictive Modeling supervised and unsupervised Machine Learning Algorithm in python and Weka.

Text Mining, NLP

AWS and Databricks

SQL SERVER and PostgreSQL

Social Network Analysis with Python and Gephi

KOKOU LETSOU

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