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Definition of Reputation Credits
Fawaz Al-Saif
Ahmadi, Kuwait
Performance-driven professional with over a decade of experience in Oil & Gas operations, enriched by extensive coursework and a keen focus on data analytics and machine learning. Leveraged a robust background in chemical engineering and supply chain management to drive sustainable practices and operational excellence. Adept at project management, with certifications in Agile, Scrum, and Lean Six Sigma methodologies. Demonstrated leadership in guiding large cross-functional teams of over 50 members. Proficient in synthesizing large datasets to inform strategic decision-making and enhance operational efficiency. Fluent in Arabic, French, and English, with basic proficiency in Spanish.
Skills
Data Analytics
- Six Sigma Black Belt
- Machine Learning
- Python
- SQL
- Tableau/Power BI
- Root Cause Analysis
Management
- Operations
- Supply Chain
- Six Sigma Black Belt
- Project Management
- Scrum
Gas Processing
- Sulfur Recovery
- Amine treating
- Gas Dehydration
- Tail Gas Treatment
- NGL Recovery
- Hazop/SIL studies
Work Experience
Operations Section Head - Acid Gas Removal
KNPC • 2009 - Present
AGRP II (2017 - Present):
- Led an operations team (50+ operators and engineers) for the commissioning and daily operation of the New Acid Gas Removal Unit at MAA refinery (230 MMSCFD of sour gas and 800 tons per day of sulfur).
- Implemented effective and efficient systems to remotely manage the team on a 24-hour basis during the COVID-19 lockdown, maintaining commissioning activities on track and increasing collaboration.
- Collaborated with key stakeholders to identify new and review existing processes and procedures, ensuring continuous improvement to plant operations.
- During my tenure, the plant achieved 30+ months of continuous operation as of September 2023.
AGRP I (2009 - 2017 & 2021-2022):
- Managed an Acid Gas Removal Unit, overseeing the treatment of 230 MMSCFD of sour gas and producing 282 Metric Tons of Molten Sulfur.
- Led a team of 100+ operators, while preparing the workforce for the commissioning of the New Acid Gas Removal Plant.
- Experience with 5 major overhauls and multiple unplanned shutdowns.
- Identified and implemented 40+ plant modifications to enhance operational success, resulting in a reduction of SO2 emissions from 3000+ ppm to less than 500 ppm, and improving plant sour gas throughput by 10+% per year from 2014 to 2017.
Education
Jack Welch Management Institute
Business Administration and Management, General • 2016 - 2020
Institut National des Sciences Appliquées de Toulouse
Master of Engineering in Process Engineering & Environment • 2003 - 2009
Master of Reserarch in Process Engineering • 2008 - 2009
Data Science Projects
For more projects, please consult my data science portfolio.
NBA Players Shooting Data
In this project, I analyzed the 2021 playoffs shooting data of four notable NBA players to offer strategic insights to a university basketball team. Using Python libraries, I conducted an exploratory data analysis focusing on shot locations, success rates, and defender influences. The visualizations created help delineate effective shooting quadrants and could aid the team in enhancing their strategies and performance.
Assessing data quality
I conducted a detailed analysis of a dataset from Sprocket Central Pty Ltd, a medium-sized bike and cycling accessories organization, to assess data quality. The analysis identified several data quality issues, setting the stage for strategies to enhance data handling and improve the accuracy of future insights.
Assessing Campaign Performance Using Chi-Square Test for Independence
In this project, I used the Chi-Square Test for Independence to analyze the effectiveness of two different mailers in a grocery retailer's promotional campaign. The analysis found no statistically significant difference in the signup rates between the two mailer types, suggesting that higher-cost mailers might not yield a higher ROI.
ABC Grocery - Customer Segmentation
I employed k-means clustering to segment a supermarket chain's customer base into three distinct groups based on their shopping patterns. The segmentation revealed different customer preferences, aiding in the development of more focused business strategies and customer communications.
Enhancing Targeting Accuracy Using Machine Learning
I analyzed a grocery retailer's previous marketing campaign data to enhance targeting accuracy for their delivery club membership using machine learning techniques. The Random Forest model emerged as the most reliable, setting the stage for more focused and cost-effective future campaigns.
Predicting Customer Loyalty Using Machine Learning
In this project, I developed predictive models to forecast the loyalty scores of a grocery retailer's customer base using transaction data. The Random Forest model proved most accurate, promising to enhance customer tracking and targeting strategies significantly.
Compressing Feature Space for Classification Using PCA
I used Principal Component Analysis (PCA) to compress a dataset of 100 unlabeled features into a more manageable size for classifying potential buyers of Ed Sheeran’s latest album. The Random Forest Classifier utilized on the compressed data achieved a 93% classification accuracy, suggesting a viable strategy for targeted marketing.
Quantifying Sales Uplift with Causal Impact Analysis
I analyzed a grocery retailer's "Delivery Club" campaign using Causal Impact Analysis to quantify the sales uplift post-campaign. The analysis indicated a significant 41.1% increase in sales among members, pointing to the campaign's effectiveness and setting the ground for further optimization strategies.
Coursework & Certificates
Data Scientist with Python/SQL Career Track by DataCamp (In Progress):
Advancing skills in data manipulation, analysis, and visualization using Python, alongside gaining a deeper understanding of machine learning algorithms.
Data Analyst with Tableau Career Track by DataCamp
Developed a strong foundation in data visualization and analytics, mastering Tableau to transform raw data into insightful dashboards.
Machine Learning Specialization by Deeplearning.ai
Acquired expertise in deep learning frameworks and algorithms, and gained practical experience in implementing machine learning models to solve real-world problems.
Data Science Infinity Program
Engaged in a comprehensive data science training program covering a wide array of topics including statistical analysis, machine learning algorithms, and advanced data visualization techniques. Developed a strong foundation in Python and SQL, and worked on real-world projects to hone practical data science skills.
MIT Micromasters in Supply Chain Management:
Focused on data analytics, optimization, and machine learning to enhance supply chain decision-making and operational efficiency. This program includes 5 graduate level courses, including supply chain analytics, fundamentals, design, dynamics and technology.
Professional Scrum Master (PSM-I)
Certified in Scrum methodology, enhancing the ability to effectively manage data-centric projects by employing Agile principles and ensuring a data-driven approach to continuous improvement.
Project Management Certificate by Google/Coursera
Explored data-driven decision-making techniques to effectively manage projects, ensuring timely delivery and adherence to budget constraints.
Fawaz Al-Saif
Ahmadi, Kuwait
Performance-driven professional with over a decade of experience in Oil & Gas operations, enriched by extensive coursework and a keen focus on data analytics and machine learning. Leveraged a robust background in chemical engineering and supply chain management to drive sustainable practices and operational excellence. Adept at project management, with certifications in Agile, Scrum, and Lean Six Sigma methodologies. Demonstrated leadership in guiding large cross-functional teams of over 50 members. Proficient in synthesizing large datasets to inform strategic decision-making and enhance operational efficiency. Fluent in Arabic, French, and English, with basic proficiency in Spanish.
Skills
Data Analytics
- Six Sigma Black Belt
- Machine Learning
- Python
- SQL
- Tableau/Power BI
- Root Cause Analysis
Management
- Operations
- Supply Chain
- Six Sigma Black Belt
- Project Management
- Scrum
Gas Processing
- Sulfur Recovery
- Amine treating
- Gas Dehydration
- Tail Gas Treatment
- NGL Recovery
- Hazop/SIL studies
Work Experience
Operations Section Head - Acid Gas Removal
KNPC • 2009 - Present
AGRP II (2017 - Present):
- Led an operations team (50+ operators and engineers) for the commissioning and daily operation of the New Acid Gas Removal Unit at MAA refinery (230 MMSCFD of sour gas and 800 tons per day of sulfur).
- Implemented effective and efficient systems to remotely manage the team on a 24-hour basis during the COVID-19 lockdown, maintaining commissioning activities on track and increasing collaboration.
- Collaborated with key stakeholders to identify new and review existing processes and procedures, ensuring continuous improvement to plant operations.
- During my tenure, the plant achieved 30+ months of continuous operation as of September 2023.
AGRP I (2009 - 2017 & 2021-2022):
- Managed an Acid Gas Removal Unit, overseeing the treatment of 230 MMSCFD of sour gas and producing 282 Metric Tons of Molten Sulfur.
- Led a team of 100+ operators, while preparing the workforce for the commissioning of the New Acid Gas Removal Plant.
- Experience with 5 major overhauls and multiple unplanned shutdowns.
- Identified and implemented 40+ plant modifications to enhance operational success, resulting in a reduction of SO2 emissions from 3000+ ppm to less than 500 ppm, and improving plant sour gas throughput by 10+% per year from 2014 to 2017.
Education
Jack Welch Management Institute
Business Administration and Management, General • 2016 - 2020
Institut National des Sciences Appliquées de Toulouse
Master of Engineering in Process Engineering & Environment • 2003 - 2009
Master of Reserarch in Process Engineering • 2008 - 2009
Data Science Projects
For more projects, please consult my data science portfolio.
NBA Players Shooting Data
In this project, I analyzed the 2021 playoffs shooting data of four notable NBA players to offer strategic insights to a university basketball team. Using Python libraries, I conducted an exploratory data analysis focusing on shot locations, success rates, and defender influences. The visualizations created help delineate effective shooting quadrants and could aid the team in enhancing their strategies and performance.
Assessing data quality
I conducted a detailed analysis of a dataset from Sprocket Central Pty Ltd, a medium-sized bike and cycling accessories organization, to assess data quality. The analysis identified several data quality issues, setting the stage for strategies to enhance data handling and improve the accuracy of future insights.
Assessing Campaign Performance Using Chi-Square Test for Independence
In this project, I used the Chi-Square Test for Independence to analyze the effectiveness of two different mailers in a grocery retailer's promotional campaign. The analysis found no statistically significant difference in the signup rates between the two mailer types, suggesting that higher-cost mailers might not yield a higher ROI.
ABC Grocery - Customer Segmentation
I employed k-means clustering to segment a supermarket chain's customer base into three distinct groups based on their shopping patterns. The segmentation revealed different customer preferences, aiding in the development of more focused business strategies and customer communications.
Enhancing Targeting Accuracy Using Machine Learning
I analyzed a grocery retailer's previous marketing campaign data to enhance targeting accuracy for their delivery club membership using machine learning techniques. The Random Forest model emerged as the most reliable, setting the stage for more focused and cost-effective future campaigns.
Predicting Customer Loyalty Using Machine Learning
In this project, I developed predictive models to forecast the loyalty scores of a grocery retailer's customer base using transaction data. The Random Forest model proved most accurate, promising to enhance customer tracking and targeting strategies significantly.
Compressing Feature Space for Classification Using PCA
I used Principal Component Analysis (PCA) to compress a dataset of 100 unlabeled features into a more manageable size for classifying potential buyers of Ed Sheeran’s latest album. The Random Forest Classifier utilized on the compressed data achieved a 93% classification accuracy, suggesting a viable strategy for targeted marketing.
Quantifying Sales Uplift with Causal Impact Analysis
I analyzed a grocery retailer's "Delivery Club" campaign using Causal Impact Analysis to quantify the sales uplift post-campaign. The analysis indicated a significant 41.1% increase in sales among members, pointing to the campaign's effectiveness and setting the ground for further optimization strategies.
Coursework & Certificates
Data Scientist with Python/SQL Career Track by DataCamp (In Progress):
Advancing skills in data manipulation, analysis, and visualization using Python, alongside gaining a deeper understanding of machine learning algorithms.
Data Analyst with Tableau Career Track by DataCamp
Developed a strong foundation in data visualization and analytics, mastering Tableau to transform raw data into insightful dashboards.
Machine Learning Specialization by Deeplearning.ai
Acquired expertise in deep learning frameworks and algorithms, and gained practical experience in implementing machine learning models to solve real-world problems.
Data Science Infinity Program
Engaged in a comprehensive data science training program covering a wide array of topics including statistical analysis, machine learning algorithms, and advanced data visualization techniques. Developed a strong foundation in Python and SQL, and worked on real-world projects to hone practical data science skills.
MIT Micromasters in Supply Chain Management:
Focused on data analytics, optimization, and machine learning to enhance supply chain decision-making and operational efficiency. This program includes 5 graduate level courses, including supply chain analytics, fundamentals, design, dynamics and technology.
Professional Scrum Master (PSM-I)
Certified in Scrum methodology, enhancing the ability to effectively manage data-centric projects by employing Agile principles and ensuring a data-driven approach to continuous improvement.
Project Management Certificate by Google/Coursera
Explored data-driven decision-making techniques to effectively manage projects, ensuring timely delivery and adherence to budget constraints.