Hi! I'm Amir FARES
Data & AI Professional | Specializing in Data Analysis and BI development, Big Data Engineering & AI/NLP Solutions

Leveraging data for intelligent, scalable solutions.

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As a versatile Data and AI Professional, I bring a robust foundation in Data Analysis, Big Data Engineering, and AI/NLP solutions, with a proven track record of delivering data-driven insights and scalable systems across diverse industries. My expertise encompasses the full data lifecycle, from building and maintaining efficient data extraction and transformation pipelines using tools like PySpark and Airflow, to designing dynamic dashboards and ad-hoc reports with Power BI, Looker Studio, and Tableau that drive informed decision-making. I have hands-on experience in data modeling, ensuring data governance, and optimizing data architectures to create reliable sources of truth, evidenced by revamping systems to improve performance by up to 90%.

My background includes developing and deploying end-to-end NLP pipelines and deep learning models, with a research publication in Arabic fake news detection that outperformed state-of-the-art models. I am proficient in leveraging LangChain, OpenAI APIs, Hugging Face Transformers, and cloud platforms like GCP and AWS to build and deploy scalable AI solutions, including Retrieval-Augmented Generation (RAG) systems. With experience at organizations like Yassir, Omdena, Sonatrach, and Wessini, I have consistently transformed complex data challenges into actionable insights and impactful business decisions, contributing to operational efficiency and strategic advancements in marketing, ride-hailing, last-mile delivery, and legal tech.

Education:

  • (M.S.) Master's degree in Fundamental of computer science and artificial intelligence | Ferhat Abbas University, Setif, Algeria (2021-2023)
  • (B.S.) Bachelor's degree in computer systems | Larbi Tebessi University, Tebessa, Algeria (2018-2021)

Professional Experience

SMEETZ (Remote, Switzerland)

Data Science Engineer

March 2026 – Present

- Led the migration from a legacy dbt project to a modernized BigQuery stack, rebuilding core fact tables for orders, ticket sales, and promo/voucher codes into a single source of truth and unblocking downstream BI, finance, and AI workflows.

- Designed and shipped the semantic layer on top of the dbt warehouse using Cube.js, exposing curated cubes through an MCP interface with row-level security, enabling AI agents and internal tools to query booking and revenue data safely.

- Built and optimized executive and operational dashboards in Omni Analytics, defining reusable measures, topics, and AI-context metadata so that non-technical users and Omni's AI agent (Blobby) can self-serve insights without engineering.

YASSIR (Hybrid, Algeria)

Data Engineer / BI Developer (Associate Engineer 1)

March 2024 – March 2026

- Led the analytics and BI pillar, driving the evaluation and adoption of the right BI platform, defining data modeling and query optimization standards, and collaborating with global partners (Google, Uber) while contributing to analytics talent recruitment.

- Built and optimized scalable ETL pipelines and data models, powering dashboards and analytics across marketing, ride-hailing, and last-mile delivery, enabling faster insights and improving business decision-making.

- Re-architected the Last Mile Delivery (LMD) data infrastructure into a unified source of truth, enhancing dashboard performance by 90% and eliminating cross-team data inconsistencies.

- Designed and implemented a hybrid Role-Based Access Control (RBAC) framework, strengthening data governance and reducing access management time by several hours weekly.

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

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)