Currently, MISC embarking into Finance Transformation Program (FTP). Theobjective of FTP is to be Data Driven Finance of Future with single source oftruth. As of now, I have delivered a few projects for internal benefits such as:✓ Spend Analytics Dashboard for Corporate Procurement team. This projecthave save ~USD 250k (licensing & consultation of Vendor Suplari) andreduction of development time (12 to 4 months) because we do itinternally rather using third party consultant. This project done by usingPython and PowerBI. In Python we are using Pandas, Sklearn, Numpypackage to do Spend Analytics.✓ Developed in house Optical Characteristics Recognition (OCR) to convertPDF Image into readable PDF. This in house tool is developed usingpython which include Pymupdf, Tkinter packages✓ Automate data download from website using web scrapping methodusing python which include Selenium, BeautifulSoup, Pandas, NumpyPackages✓ EagleStar Robotic Process Automation engine for Document Reference inSAP. The benefit from this project is we manage to drop from 10 mandays(MD) to 0.004-0.006 MD (2-3mins) to completed the process of 600-800invoices/month.✓ Global Market Performance Dashboard (GMPD) Modelling by usingpowerBI as the dashboard and using power automate to extract the dataautomatically from website, email and PDF documents. This will assistTreasury team in analysis at first glance since data is up to date on time.Benefit from this we manage to reduce time taken from 150 minutes to2.50 minutes which increase efficiency by 98%.✓ LinkedIn Scrapper. This project help internal hiring manager in gettingpossible candidate by just searching the desired keyword. The engine willautomatically extract all matching profile with the criteria set in thesearching parameter. This will help hiring manager to find possiblecandidate to fill in the vacancy position.

As a data scientist, I am responsible to lead and manage data science project under PETRONAS. The projects are :  Predictive Maintenance for Hypercompressor in PC LDPE. In this project data science knowledge is applied to predict the health and the performance of the compressor before its down. This project is will save 2 Million ringgit per day per down time. Currently, the engineers in this plant having difficulty to monitor and predict when the compressor going to down. By having this predictive maintenance, the team can have mitigation plan and action to avoid the machine to go down. Predictive maintenance for CO2 compressor in PETRONAS Chemical Fertilizer Kedah.  Talent Engine 2.0 for PETRONAS Group Wide. This project is extinction from project Talent Engine 1.0 that had been done in 2017. Talent Engine 1.0 is focusing on Top Talent for group PETRONAS. But, in Talent Engine 2.0 the scope is expand to all group wide for PETRONAS staff. The idea for this project to have Talent and Position profile for every staff and position in PETRONAS. Later, we are going to do matching to match every staff with suitable position. We are using optimization method to come out with the matching.  Auditor scheduling using optimization method for group internal audit. This project will schedule and assign each auditor to respective task based on several identified criteria. From this project, management can have right people to perform audit and each task can be deliver smoothly. Text analytic for leadership competency department. This project mainly to digitize all documents from unstructured to structured data. All documents in PDF, word, power point will be converted into structure database by using text mining and automation. This project enables the team to have one single repository for all the data and easy for future analytic reference.

Develop PETRONAS Group HRM Information Architecture Strategy, Innovative proof of concepts and roadmaps through collaboration with PETRONAS HR business units with in-depth understanding to enable PETRONAS business vision and strategies.  Work across Group HR business units to identify and model business scenarios that are meaningful and have impact on critical business processes and decisions. Apply advanced statistical and predictive modeling techniques to enable data driven capabilities such as to build, maintain, and improve on multiple real-time decision systems e.g. Talent Engine.  Design algorithms to encapsulate HR Business Processes as part of the Business Architecture environment including improving related Business Processes using BPM (Business Process Modeling).  Design and develop experimental design approaches to validate findings and/or test hypotheses. (e.g. prototyping solutions from HR Design Studios)  Identify and create appropriate algorithms to discover patterns in HR data Evaluate and qualify data platforms for single source truth information storage for HR data both internal and external to the organization that may be used in support of business use cases. Identify HR related data and architecture that would enable data to be available and relevant, including both internal and external data sources.  Identify information architecture requirements and implement them by researching and analyzing user needs, preferences, objectives and business process.  Partners with respective business data stewards to define data quality expectations in the context of the business use cases and overall HR data strategy.  Recommend ongoing improvements to methods and algorithms that lead to findings, including new information and new ways of improving data processes.

Focus on the Big Data Analytics program with strategic initiatives on: Plant Analytics (Operational Analytics, Predictive Maintenance and Profitability Analytics) CORAL Cost Benchmarking Analytics Data Analytics Architecture Standard and Framework for Upstream Technical Data Supply Chain Optimization Petrochemical Marketing Business Insight Operational Management and Contact Centre Analytics Strategy paper on Predictive Analytics and CS&R Big Data Lab Big Data Community of Practice (CoP)

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ICT Technology Strategy & Architecture

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