Data Science Machine Learning

Michael Attoh

*******.*******@*****.*** 254-***-**** https://www.linkedin.com/in/michael-attoh-251a2436/ https://github.com/Michael-Attoh EDUCATION

Tarleton State University, Stephenville, Texas

MS in Mathematics - Data Science

Relevant coursework: Data Science, Statistical Models, Linear & Abstract Algebra, Data Warehousing, Dynamical Systems & Chaos, Real Analysis, Mathematical Modeling, Research Analysis.

Kwame Nkrumah University of Science & Technology, Kumasi, Ghana BS in Mathematics

PROFESSIONAL EXPERIENCE

Texas Commission On Environmental Quality - Austin, Texas Sept’ 2023 - present Data Analyst

● Analyzed anthropogenic emissions inventory data using Python, R, and SQL, developing statistical models and predictive analytics to support State Implementation Plans (SIPs) for air quality improvements. Ensured data integrity and model reliability through robust validation, reducing discrepancies.

● Built complex SQL queries and Python-based data pipelines to process multi-database emissions datasets, uncovering key trends and anomalies. Improved data quality by integrating machine learning anomaly detection, enhancing global QA processes for EPA compliance.

● Designed compelling visualizations and technical reports for stakeholders, including the EPA, using PowerBI and Python (Matplotlib, Seaborn) to convey air quality insights and model-driven recommendations, driving regulatory alignment and stakeholder decisions.

● Spearheaded cross-functional teams in national and state-level workgroups, advancing emissions forecasting models with advanced statistical methods and machine learning techniques using Python, R, and SAS, improving estimation accuracy for regional air quality initiatives.

● Managed end-to-end technical projects, including grant development and data workflows, leveraging SQL, Python, and R for data preprocessing, model optimization, and timely delivery of high-quality emissions datasets, supporting critical regulatory deadlines. Texas Commission On Environmental Quality - Austin, Texas May’2023 - Aug’2023 Geocoding Analyst/Project Manager Intern

● Successfully executed a spatial data enhancement project, improving mapping data accuracy using Python and SQL.

● Applied GIS and data analysis skills to transform mapping data into precise spatial coordinates using ESRI geoprocessing services.

● Developed and maintained detailed documentation, including technical requirements and process flows, ensuring alignment with business objectives. Tarleton State University - Stephenville, Texas Jan’2022 - May’2023 Data Science Researcher

● Developed stochastic network models in Python to simulate viral disease spread, enabling scenario analysis and informing targeted public health interventions.

● Built and deployed supervised machine learning models using GCP and Azure to predict outcomes for breast cancer, diabetes, heart disease, and housing prices—highlighting critical features for early diagnosis and risk mitigation.

● Applied natural language processing and sentiment analysis to Twitter data to identify market sentiment trends and used time series modeling to forecast stock performance, supporting data-driven financial strategies.

● Conducted end-to-end workflows including data preprocessing, feature engineering, model evaluation, and visualization using tools like Scikit-learn, Pandas, Seaborn, and Power BI.

MA Medical Services - San Antonio, Texas May'2018 - Dec'2021 Data Analyst

● Designed and developed interactive dashboards and automated reports using Power BI, SAS, SQL, and Python to monitor patient demographics, treatment outcomes, and resource utilization, improving visibility for clinical and operational teams.

● Conducted in-depth statistical analysis and data profiling to uncover trends in patient care, disease prevalence, and treatment efficacy, supporting evidence-based healthcare planning and improving patient outcomes.

● Enhanced operational efficiency by cleaning and transforming large, complex datasets, reducing reporting errors and accelerating decision-making cycles.

● Streamlined data integration workflows across EHR systems and third-party sources, creating a unified, real-time view of performance metrics and driving data consistency across departments.

PROJECTS

● Stochastic Processes Disease Modeling

Built stochastic network models (Probabilistic House of Edges) to simulate viral spread in social networks. Delivered insights on infection patterns and intervention strategies to aid public health decisions.

● Predictive Analytics & Sentiment Analysis

Used NLP for Twitter sentiment analysis to predict stock trends and guide financial strategies. Created ML models to forecast outcomes for breast cancer, diabetes, heart disease, and housing prices, identifying key risk factors for proactive decisions.

SKILLS

Functional : Team Leadership, Project Coordination, Business Acumen, Effective Communication, Problem Solving, Time Management, Adaptability, Attention to Detail, Technical Skills: Ethical Judgment

● Programming & Data Analysis: Python, R, Julia, SQL, SPSS, SAS

● Data Visualization: Seaborn, ggplot2, Bokeh, Matplotlib, Power BI, Tableau

● Databases & Warehousing: MySQL, PostgreSQL, SQL Server, Google BigQuery, Data Warehousing, DBVisualizer

● Machine Learning & AI: TensorFlow, PyTorch, Neural Networks, Deep Learning, Large Language Models, Natural Language Processing, Bayesian Inference

● Cloud Platforms & Tools: Google Cloud Platform (GCP), Azure Data Studio, Deepnote, SharePoint, VSCode

● Additional Skills: CSS, Excel, Beautiful Soup, Data Wrangling, Data Cleaning, Web Scraping, Data Mining, Regression Models, Statistical Analysis (ANOVA, Hypothesis Testing), Experimental Design, Business Intelligence, Jira, Salesforce ACHIEVEMENTS

● Team Lead on stochastic network models projects and project manager for the Geocoding project.

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