About Me

Experienced and highly motivated Data Engineer/Scientist with a solid background in software engineering and AI. Skilled in developing data pipelines, AI-driven models, and leveraging cloud platforms like AWS and Azure to drive data solutions and operational efficiency.

Adept at collaborating with clients and cross-functional teams to deliver end-to-end data solutions, driving operational efficiency and informed decision-making.

What I'm Doing

  • Data Engineering

    Data Engineering

    Designing and developing robust data pipelines and architectures using modern tools like Azure and AWS.

  • AI & Machine Learning

    AI & Machine Learning

    Creating AI-driven models for various applications, including product recommendations and customer segmentation.

Resume

Education

  1. Vrije Universiteit van Amsterdam, Netherlands

    2020 — 2023

    Researcher in Evolutionary Robotics. Focused on AI and machine learning applications in robotics.

  2. Azad University of Tehran, Iran

    2016 — 2019

    Master's Degree in Artificial Intelligence and Robotics.

  3. Shahid Chamran University, Ahvaz, Iran

    2011 — 2016

    Bachelor's Degree in Software Engineering.

Experience

  1. Data Engineer/Scientist - The Data Cooks, Amsterdam, Netherlands

    January 2022 — July 2024

    Developed data marts and pipelines using SQL and Azure. Leveraged AI on large datasets using Python, Azure, and Databricks. Automated data pipelines with Azure Data Factory, reducing processing time by 30%.

  2. Teaching Assistant - Vrije Universiteit van Amsterdam, Netherlands

    2021

    Assisted in courses such as "Evolutionary Computing," "Learning Machines," and "Embodied AI." Supervised 15 students on research related to evolutionary robotics.

  3. Freelance Data Engineer - IT and Business Analytics Ltd, London, UK

    2018 — 2019

    Analyzed and developed an ERP system using MariaDB and Python. Implemented AWS Lambda functions for data processing tasks.

  4. Data Engineer - Farzaneh Image Processing Company, Tehran, Iran

    2017 — 2018

    Extracted, interpreted, and analyzed data to identify key metrics. Created dashboards for data reporting and utilized AWS S3 and CloudWatch for data storage and monitoring.

  5. Freelance Application Programmer - Novin Abr e Persian, Ahvaz, Iran

    2015 — 2016

    Designed and developed a warehousing application using C#, Microsoft SQL Server, and DevExpress.

  6. Maintenance and Development Intern - NISOC, Ahvaz, Iran

    2014

    Maintained and repaired the network. Developed an application to record gasoline usage using C#, Microsoft SQL Server, and DevExpress.

Skills

  • Python, R, C#
    90%
  • SQL & NoSQL Databases
    85%
  • Azure & AWS Cloud Platforms
    80%
  • Machine Learning & AI
    75%

Certifications

  1. Data Storage in Microsoft Azure

    Issued Aug 2024

    Coursera - Skills: Azure data Storage

  2. Microsoft Azure for Data Engineering

    Issued Aug 2024

    Coursera - Skills: Data Engineering, Big Data, Cloud Computing

  3. Ultimate Beginners Guide to Power BI

    Issued Apr 2022

    Enterprise DNA - Credential ID: 93126333549279

Portfolio

AI-Driven Data Solutions for Large Datasets

Leveraged AI on large datasets using Python, Azure, and Databricks to create impactful data-driven solutions. Developed models that increased sales by 3% through customized product recommendations and improved targeted marketing efforts by 20% with a customer segmentation model.

  • Created an AI-driven model to generate customized product recommendations, increasing sales by 3%.
  • Developed an AI-driven store assortment planner that reduced lost sales.
  • Improved targeted marketing efforts by 20% with a customer segmentation model.

Data Engineering and Pipeline Automation

Developed data marts and pipelines using SQL and Azure to streamline data accessibility. Automated data pipelines with Azure Data Factory, reducing data processing time by 30%. Integrated CRM data into the warehouse with AWS Lambda, ensuring GDPR compliance.

  • Automated data pipelines using Azure Data Factory, reducing data processing time by 30%.
  • Integrated CRM data into the warehouse, designing a data model and building pipelines in AWS Lambda, ensuring GDPR compliance.

AI and Machine Learning Models for Business Optimization

Designed and implemented AI models to enhance business operations. Built a forecasting model using time series analysis, increasing the accuracy of sales predictions by 15%, and conducted data analysis leading to a 10% reduction in operational costs.

  • Built a forecasting model using time series analysis, increasing the accuracy of sales predictions by 15%.
  • Conducted data analysis that led to a 10% reduction in operational costs.

Dashboard Development and Data Visualization

Developed dashboards in PowerBI to enhance data visibility and decision-making speed. Designed intuitive dashboards that enabled stakeholders to quickly access and analyze key metrics.

  • Developed dashboards in PowerBI, improving data visibility and decision-making speed.

Competitor Pricing Scraper Tool

Developed a scraper tool to monitor competitors’ pricing on e-commerce platforms, providing real-time insights into pricing strategies and allowing for dynamic pricing adjustments.

  • Built a scraper tool to monitor competitors’ pricing on e-commerce platforms.

Academic Background

Research at Vrije Universiteit

During my research at Vrije Universiteit, I explored how natural life demonstrates remarkable complexity beyond genetic encoding. This project studied a novel robot DNA structure that provides robots with lifetime phenotypic plasticity, allowing them to adapt to environmental changes. By developing a genotype-phenotype mapping, we enabled robots to modify their behaviors in response to their surroundings, demonstrating increased evolutionary efficiency and responsiveness to environmental conditions.

Vrije Universiteit Research

Publications

  • Paper 1: "The effect of selecting for different behavioral traits on the evolved gaits of modular robots" - BH Kargar, K Miras, AE Eiben, ALIFE 2021: The 2021 Conference on Artificial Life.
  • Paper 2: "A Multi-Brain Approach for Multi-Tasking in Evolvable Robots" - E de Bruin, J Hatzky, BH Kargar, AE Eiben, EasyChair.
  • Paper 3: "Exploring proprioceptive feedback in the evolution of modular robots" - Babak H Kargar, Karine Miras, A.E. Eiben, Accepted for publication in PPSN 2024.

Master's Thesis: Caps Matting

My master's thesis titled "Caps Matting" explores a novel deep learning model using capsule networks for image matting. This model addresses the complex problem of accurately separating foreground elements in an image from the background, a technique widely used in filmmaking and image editing. The proposed model, based on capsule networks, demonstrates significant improvements over traditional methods in preserving spatial hierarchies and performing accurate segmentation.

Caps Matting Thesis

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