Muhammad Hafizudeen Mohamad Saman

I am an alumnus of the University of Michigan, Ann Arbor, having graduated with triple majors in Actuarial Mathematics, Data Science, and Statistics, with minors in Computer Science and Business Administration. I have experience in the oil and gas industry, where I worked in a data scientist/analyst role.

In addition, I have experience in actuarial retirement consulting. I hold five professional certifications from the Society of Actuaries (SOA) toward the Associate/Fellowship of the Society of Actuaries (ASA/FSA designation). Additionally, I possess three Validation by Educational Experience (VEE) credits and have completed the Pre-Actuarial Foundations module.

I find great satisfaction in collaborating with others while working with data, and I excel at leveraging my skills in building machine learning, statistical, or actuarial models to contribute effectively to team projects.

Technical Skills & Tools:
• Coding languages: Python, C++, R, SQL, & VBA
• Data science tools: Azure ML and RStudio 
• Database Management tools: Oracle, MongoDB, Databriks, and Talend
• Visualization tools: PowerBI, ArcGIS, Matlab, & PI Processbook

I am enthusiastic about opportunities where I can apply my actuarial knowledge and critical thinking skills within the finance or health industries to make a meaningful and positive impact on the lives of others.

I lead the strategic design, management, and execution of data in digital projects of PETRONAS' Gas Business, enhancing operational efficiency and generating value by delivering targeted solutions for data availability, analysis, reporting, performance management, and campaigns.

𝗦𝘂𝗰𝗰𝗲𝘀𝘀𝗳𝘂𝗹 𝗽𝗿𝗼𝗷𝗲𝗰𝘁𝘀:

1) I have developed machine learning predictive model for anticipating gas turbine meter failure, safeguarding assets with a total value of RM13 million (USD 2.8 Mil).

2) I have also led the planning and execution of the new methane leakage surveillance method for underground pipelines, mitigating the risk of potential annual revenue loss of RM400 million (USD 86 Mil) and saving 7544 hours of physical surveillance hours annually.

3) I have assisted with the implementation of AI-powered Interactive Learning of LNG Asset Operational Assurance documents which has improved the plant workers compliance to governance documents by 41%.

4) I also orchestrated the automation of Greenhouse Gas data for real-time visibility, elevating automated data to 93% and yielding a remarkable 90% improvement in Process Cycle Efficiency.

5) I conducted Root Cause Analysis (RCA) on challenging datasets, resulting in an outstanding 95.26% overall data quality score—an impressive 25% enhancement compared to the score achieved without RCA.

Graduated with Bachelor of Science with triple majors in Actuarial Mathematics, Data Science, and Statistics, with minors in Computer Science and Business Administration from the University of Michigan. Class of 2022