Amir FARES Portfolio

Hi! I'm Amir FARES an Associate Data Analyst and BI Specialist

Leveraging data for intelligent solutions.

As a Data Analyst and BI Engineer with a strong foundation in data modeling, analysis, and reporting, I bring extensive experience in delivering data-driven solutions across multiple industries. With proven expertise at Yassir, Sonatrach, Omdena, and Wessini, I specialize in transforming complex data into actionable insights and impactful business decisions. My work spans dynamic dashboard creation, data visualization (Tableau, Power BI, Looker Studio), and building reliable data models that ensure the integrity and accuracy of business intelligence processes.
In addition to my industry experience, I have demonstrated innovation through research, with a published paper in the NLP field, and have developed creative solutions within organizations that drive operational efficiency and strategic decision-making. I have consistently contributed to the success of organizations by optimizing data workflows, developing reporting solutions, and enhancing BI processes across marketing, ride-hailing, last-mile delivery, and other domains. By integrating large-scale datasets (Big Data) and streamlining data pipelines, I empower stakeholders to make informed, data-backed decisions.

Professional Experience

𝐘𝐀𝐒𝐒𝐈𝐑 (Hybrid, Algeria)

Associate Data Engineer / Analyst

March 2024 – Present

- 𝗗𝗲𝘀𝗶𝗴𝗻𝗲𝗱 𝗮𝗻𝗱 𝗱𝗲𝗹𝗶𝘃𝗲𝗿𝗲𝗱 𝗻𝘂𝗺𝗲𝗿𝗼𝘂𝘀 𝗱𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱𝘀 𝗮𝗻𝗱 𝗮𝗱 𝗵𝗼𝗰 𝗿𝗲𝗽𝗼𝗿𝘁𝘀 across marketing, ride-hailing, and last-mile delivery domains, driving data-informed decision-making and contributing to Yassir's success in 2024.

- 𝗟𝗲𝗱 𝘁𝗵𝗲 𝗱𝗮𝘁𝗮 𝗺𝗼𝗱𝗲𝗹𝗶𝗻𝗴 𝗮𝗻𝗱 𝗱𝘆𝗻𝗮𝗺𝗶𝗰 𝗱𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱 𝗿𝗲𝘃𝗮𝗺𝗽 𝗳𝗼𝗿 𝘁𝗵𝗲 𝗟𝗮𝘀𝘁 𝗠𝗶𝗹𝗲 𝗗𝗲𝗹𝗶𝘃𝗲𝗿𝘆 (𝗟𝗠𝗗) 𝗱𝗼𝗺𝗮𝗶𝗻, creating a reliable single source of truth. This effort improved dashboard response times by 90%, enabling teams to make faster, more accurate decisions based on consistent and reliable data.

- 𝗣𝗶𝗼𝗻𝗲𝗲𝗿𝗲𝗱 𝗮 𝗰𝘂𝘀𝘁𝗼𝗺 𝗵𝘆𝗯𝗿𝗶𝗱 𝗥𝗼𝗹𝗲-𝗕𝗮𝘀𝗲𝗱 𝗔𝗰𝗰𝗲𝘀𝘀 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 (𝗥𝗕𝗔𝗖) 𝗮𝗽𝗽𝗿𝗼𝗮𝗰𝗵 tailored to Yassir’s unique needs, eliminating inefficiencies of the previous system. This innovation reduced access management time by hours weekly and enhanced data governance across the organization.

𝐎𝐌𝐃𝐄𝐍𝐀 (Remote, Algeria)

Lead ML Engineer, Data Scientist, Project Manager Assistant

October 2023 – February 2024

- 𝐋𝐞𝐚𝐝 𝐌𝐋 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 & 𝐏𝐫𝐨𝐣𝐞𝐜𝐭 𝐌𝐚𝐧𝐚𝐠𝐞𝐫 𝐀𝐬𝐬𝐢𝐬𝐭𝐚𝐧𝐭: Provided guidance and leadership to a team over a 5-month period, contributing to the successful completion of a project.

- 𝐀𝐈-𝐃𝐫𝐢𝐯𝐞𝐧 𝐖𝐚𝐭𝐞𝐫 𝐀𝐯𝐚𝐢𝐥𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐅𝐨𝐫𝐞𝐜𝐚𝐬𝐭𝐢𝐧𝐠: Spearheaded the development of an AI-driven solution for forecasting water availability, from research and data collection to modeling and deployment. Achieved remarkable accuracy and transformed an open-source project into a user-friendly forecasting app capable of predicting water availability for various timeframes, from months to a decade ahead.

- 𝐏𝐞𝐫𝐬𝐨𝐧𝐚𝐥 𝐚𝐧𝐝 𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐆𝐫𝐨𝐰𝐭𝐡: Embraced opportunities for personal and professional development, learning from industry leaders and participating in workshops. Played a pivotal role in an open-source project, collaborating with diverse contributors and enhancing communication skills as a lead in machine learning.

𝐖𝐄𝐒𝐒𝐈𝐍𝐈 (Algiers, Algeria)

ML Engineer

November 2023 – January 2024

- 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗱 𝗮𝗰𝘁𝗶𝗼𝗻𝗮𝗯𝗹𝗲 𝗱𝗮𝘁𝗮 𝘃𝗶𝘀𝘂𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻𝘀 𝘂𝘀𝗶𝗻𝗴 𝗘𝘅𝗰𝗲𝗹 𝗮𝗻𝗱 𝗣𝘆𝘁𝗵𝗼𝗻 to analyze legal data trends, showcasing insights on law document types and yearly distributions, enhancing stakeholder decision-making and vision on the project.

- 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗲𝗱 𝗮𝗻𝗱 𝗮𝗻𝗮𝗹𝘆𝘇𝗲𝗱 𝗹𝗲𝗴𝗮𝗹 𝗱𝗮𝘁𝗮𝗯𝗮𝘀𝗲𝘀 𝘂𝘀𝗶𝗻𝗴 𝗡𝗟𝗣 𝘁𝗲𝗰𝗵𝗻𝗶𝗾𝘂𝗲𝘀, achieving a 93% success rate in linking datasets based on Algerian law titles and extracting valuable insights.

- 𝗜𝗺𝗽𝗮𝗰𝘁𝗳𝘂𝗹 𝗟𝗲𝗴𝗮𝗹 𝗧𝗲𝗰𝗵 𝗖𝗼𝗻𝘁𝗿𝗶𝗯𝘂𝘁𝗶𝗼𝗻: improving data accessibility and delivering precise legal assistance for lawyers and the Ministry of Laws in Algeria.

𝐒𝐎𝐍𝐀𝐓𝐑𝐀𝐂𝐇 (GEM, Oued Safsaf, Tebessa, Algeria)

Data Analyst Intern

February 2023 – March 2023

- 𝐈𝐧-𝐃𝐞𝐩𝐭𝐡 𝐊𝐏𝐈 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬: Conducted an extensive analysis of SONATRACH's seven key performance indicators (KPIs) related to its 1,644.537 km pipeline network and 45 sectioning stations. This analysis contributed to operational improvements and informed decision-making.

- 𝐃𝐚𝐭𝐚-𝐃𝐫𝐢𝐯𝐞𝐧 𝐃𝐞𝐜𝐢𝐬𝐢𝐨𝐧 𝐄𝐧𝐡𝐚𝐧𝐜𝐞𝐦𝐞𝐧𝐭: Discovered critical correlations between KPIs, including the annual transport capacity of 33.2 billion cm^3, and SONATRACH's strategic goals. This data-driven approach significantly improved decision-making processes, aligning business strategies with operational objectives.

- 𝐏𝐫𝐨𝐟𝐞𝐬𝐬𝐢𝐨𝐧𝐚𝐥 𝐆𝐫𝐨𝐰𝐭𝐡: Through this full-time internship with a rigorous 8-hour daily schedule, I deepened my expertise in CIMIX software, mastering analysis of seven KPIs. My proficiency in Excel also improved significantly. This hands-on experience equips me with concrete skills, setting the stage for a career as a data analyst, where I can leverage my knowledge gained from SONATRACH's extensive infrastructure.

Publications

An Ensemble Deep Learning Models Based on Metadata for Measuring Arabic Fake News Uncertainty - July 2024
IEEE - Amir Fares, Rania Yasmine Chougui, Ahlem Drif, Silvia Giordano
The research paper published at the 2024 IEEE International Conference on Advanced Systems and Emergent Technologies (IC_ASET'2024) demonstrating innovative approaches in Arabic fake news detection, with results that outperformed the latest state-of-the-art models in the field.

Projects

🪙 Bitcoin Navigator 📊

A data-driven dashboard designed to analyze Bitcoin trends, empowering investors to refine their strategies and identify optimal investment opportunities.
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Onyx Data DataDNA Challenge - Spotify Most Streamed Songs 2023 Dataset - October 2023 🎧

Explore my data-driven journey through the Spotify Most Streamed Songs 2023 Dataset, where I uncover the secrets behind song popularity on Spotify. Discover insights for the modern music landscape.
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Store Sales Forecasting

Dedicated to optimizing store sales predictions for Corporación Favorita, our project employs time series forecasting and machine learning. Using XGBoost, achieved a promising score of 1.45784, laying a solid foundation for further refinement and improvement.
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Spotify Wrapped 2024: Music That Worked as Hard as I Did

Analyzed personal music data for the Maven Music Challenge, creating a 2024 'Spotify Wrapped' experience. Highlights include top songs, artists, insights into listening trends, peak months, and a unique analysis of the relationship between my listening time and work schedule, uncovering patterns in productivity and music preferences.
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ChatGPT Answer Classification Challenge 🤖

Ranked top 20 in the ML Olympiad's ChatGPT Answer Classification Challenge, I developed a model enhancing AI-generated content credibility.
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Fashion MNIST CNN Classifier

showcasing our image classification prowess with a 92.3% validation accuracy. Overcoming challenges in discerning similar fashion classes underscores our commitment to robust, accurate solutions.
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Maven Environmental Challenge: Tracking Apple's Carbon Neutrality Journey 🍏🌍

Explore Apple's carbon neutrality journey through the lens of data-driven insights and journalism in my Maven Environmental Challenge project. Uncover the strategic decisions driving sustainability, such as the charger removal in 2020.
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JUMIA Sentiment Analysis - ML Olympiad

🏆 Top 3 Finisher 🏆 Check the button below for more details about the challenge and how to analyze customer sentiments from their reviews.
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Tunisia Energy Fraud Detection STEG

In the fight against electricity and gas fraud in Tunisia, I secured a top 25% position on the leaderboard, using an XGBoost model with an AUC of 0.86. Analyzing billing history, the solution safeguards STEG's revenues, minimizing losses.
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Certifications

Google Advanced Data Analytics Certificate (Google - Coursera)
Microsoft Power BI Desktop (Maven Analytics)
Introduction to Data Analysis Using Excel (RICE UNIVERSITY - Coursera)
Accelerating End-to-End Data Science Workflows (NVIDIA)
Introduction to Git and GitHub (Google - coursera)
Machine Learning Specialization (DeepLearning.AI - coursera)
Deep Learning Specialization (DeepLearning.AI - coursera)