Enoch Nuamah Appiah

I am a highly motivated and diligent data analyst with 3 years of experience in interpreting and analyzing data to drive growth. I possess in-depth knowledge and expertise in data science, and I am proficient in

Python, SQL, SAS, Power BI, Tableau, and machine learning. I take ownership of challenging problems,

maintain high standards, and assist my employer in achieving their commercial objectives. With a desire and passion for continuous professional development, I am confident I can add value to your organization.

Energy Data Analyst (Remote) June 2021 – present

Acquirente Unico SPA, Rome, Italy

RESPONSIBILITIES

• Evaluated data quality and cleaned poor data to ensure accurate insights in making decisions.
• Successfully built interactive dashboards using the Tableau platform and Power BI to assist consumers in monitoring their gas and electricity usage increasing ARERA website visits by 15%.
• Successfully integrated the Tableau visualization platform for the company and organized the roll-out of competency training for my team, resulting in improved data analytics capabilities.
• Conducted and generated daily, weekly, and monthly statistical reports based on routine analysis in dashboards based on business objectives.
• Developed SAS process flow to add monthly electricity and gas data to the database and created reporting procedures for graphical and tabular reports increasing work efficiency by 20%.
• Used SAS extensively for match-merge, append, data validation, outlier analysis, and data cleaning.
• Developed SAS BI dashboards which are used to monitor key performance indicators.

Data Science Intern Oct 2020 – April 2021

NHOA Energy S.r.l. (formally Engie EPS), Milan, Italy

RESPONSIBILITIES

• Successfully conducted statistical analysis on data from Battery Storage systems using Python.
• Expertly developed anomaly detection codes and models to monitor and detect abnormalities in battery storage data from existing plants.
• Developed and implemented an automated Python code to clean and explore the raw data coming from the energy storage site.
• Interacted with different data sources by generating monthly reports and sharing insights with the team during sprint reviews.

Research Assistant (R&D) Oct 2018– Dec 2019

DataOptima Lab, Politecnico di Milano, Italy

RESPONSIBILITIES

• Proposed data-driven methods to monitor fan coils to improve energy efficiency and air conditioning in buildings.
• Interacted with different data sources by applying machine learning models to improve energy consumption in residential buildings.
• Built and tested algorithms and mathematical models to improve data extraction and synthesis.

Master’s degree in Artificial Intelligence and Data Science (Expected grade: distinction) Sep 2023

University of Hull, UK

Master’s Degree Energy Engineering (Grade: 101/110) Dec 2019

Politecnico di Milano, Italy

Bachelor’s degree in Mineral Engineering (82/100) July 2014

University of Mines and Technology, Ghana