About
Data Scientist & Quantitative Analyst.
Hello, I am Samuel, a Data scientist currently based in Houston, Texas!
I hold a bachelor's degree in Economics and Statistics from the University of Ghana, where I developed a strong foundation in data analysis and its applications, particularly in public economics. My academic journey equipped me with robust skills in statistical analysis, econometrics, and data modeling, enabling me to uncover valuable insights from complex datasets. My intellectual curiosity has driven me to expand my expertise beyond my core focus areas. I have actively sought to broaden my knowledge in related disciplines, embracing opportunities to deepen my understanding and diversify my skill set.
Building on this foundation, I earned a master’s degree in Data Science from the University of Rochester. This program immersed me in advanced analytics techniques, machine learning, and cutting-edge data science technologies. Through this experience, I refined my ability to harness data for solving complex problems and driving impactful decision-making. On this website, you’ll find a collection of my work, projects, and insights in data science. I am passionate about merging my background in economics, statistics, and data science to approach challenges with a multidisciplinary perspective. Whether through rigorous statistical analysis, predictive modeling, or leveraging machine learning algorithms, I am committed to delivering actionable solutions that make a difference.
If you are exploring opportunities for collaboration or have projects that could benefit from data-driven approaches, I would be thrilled to connect and explore how we can work together. Let’s leverage the power of data to drive innovation and create meaningful impact.
Skills
- Languages: Python, R, STATA, SQL, SAS, Power BI, Tableau, Spark
- Proficient in: Microsoft Word, Excel, PowerPoint, Box Cloud
- Technologies/Frameworks: Linux, GitHub, Databricks, Snowflake, AWS, PyCharm
Resume
Summary
Samuel Nuamah-Amoabeng
Innovative and deadline-driven professional with experiences as a Data Scientist, Data Analyst and Scientific Programmer. I specialize in leveraging data to drive insights and deliver impactful solutions.
- Houston, Texas, TX
Education
Master of Science
2022 - 2023
University of Rochester, Rochester, NY
Data Science
Bachelor of Arts
2016 - 2020
University of Ghana, Legon, Ghana
Economics and Statistics
Professional Experience
Quantitative Analyst
June 2024 - Present
ENGIE Energy Marketing NA, INC, Houston, TX
- Developed and implemented MISO Random Forest and SPP XGBoost models using Python, SQL and AWS (S3, EC2, Lambda, Athena) to forecast DALMP, ensuring scalable cloud deployment and identifying areas for performance refinement.
- Applied SPP methodology across multiple nodes and enhanced MISO model adaptability, leveraging AWS, Python, and SQL to scale forecasting solutions effectively.
- Conducted data-driven market analysis using Python, SQL, and data visualization tools to support commercial decision-making and optimize trading strategies.
- Developed and deployed automated bidding strategies using Python, combining percentile-based VaR and IQR-based price spike logic, leading to a 2x increase in P&L and a substantial reduction in max drawdown, with a 85% improvement in bid accuracy during high-volatility periods.
- Improved analytical efficiency by optimizing data pipelines and forecasting workflows using SQL, Python (building reusable Python classes) and AWS, reducing manual intervention by 40%.
- Developed a strong understanding of power market dynamics, transitioning from theoretical learning to practical application through hands-on analysis and proactive problem-solving.
Data Scientist & Scientific Programmer
April 2023 - December 2023
Center for Integrated Research Computing (CIRC), University of Rochester, New York, NY
- Analyzed a large SLURM dataset with over 15 million observations using SAS and Python to perform data exploration, cleaning, and statistical analysis.
- Utilized SAS programming in a Linux cluster to preprocess and cleanse the data, ensuring data quality and accuracy.
- Developed an automated program to assess utilization and optimization of the University’s high-performance computing environment, leveraging data science techniques.
- Extracted and analyzed job-related data from the cluster to identify improvement areas based on resource allocation and user demand, collaborating with a supervisor to develop data-driven recommendations for enhancing computing infrastructure efficiency.
Student Assistant
November 2022 - December 2023
Goergen Institute of Data Science (GIDS), University of Rochester, New York, NY
- Developed and implemented an automated admission decision program using Python that processed multiple reviewers’ Excel files, resulting in quick and error-free decisions for over 500 master’s degree applicants, and saved the program’s coordinator significant time and effort.
- Maintained and managed students and alumni information in both online and physical files, ensuring data accuracy and confidentiality
Risk Analyst Assistant
October 2020 – August 2021
Social Security and National Insurance Trust - Risk and Quality Dept., Accra, Ghana.
- Reviewed the previous five reports and research conducted by the department to gain insights and knowledge about the field.
- Assisted in the development of a Credit Risk Model by performing data cleaning and analysis using Excel and R to ensure accuracy of data before submission to management for review.
- Acquired knowledge and a comprehensive understanding of Risk Management practices and competencies through active participation in various tasks and projects.
- Contributed to the Need Analysis for the Acquisition of an Asset and Liability Management System (ALMS) project by providing valuable insights and suggestions to the team.
Publications
Edinam Klutse, Samuel Nuamah-Amoabeng, Hanjia Lyu and Jiebo Luo, "Dismantling Hate: Understanding Hate Speech Trends Against NBA Athletes", International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation (SBP-BRiMS), Hybrid, Pittsburgh, PA, September 2023.