• Hi!
    I'm Aiden Ahmet.

    I am a end2end 4+ years of experienced Data Scientist

About

Who Am I?

Hi I'm Aiden Ahmet Erdogan, I have Software Engineering degree and powerful Data Science with 4+ of experience collaborating with cross-functional agile teams. Broadly and with strong experience working with predictive, prescriptive, and descriptive analytics tasks, and developing end-to-end data-driven solutions. Extensively worked on:

- Optimization Models: Price Optimization

- Personalized Recommendation systems such as recommending stock numbers for new openning offline retail store.

- Time-series forecasting models such as season senstive demand forecasting for short-term or long-term.

- Natural Language Processing use cases.

Problem Solver

Cross-Functional Team Player

Self-Motivated Quick Learner

My Works

Passion projects beside experience.

End2End Home Price Recommendation

Project is ready on GitHub for onprem and AWS EC2 Deployment

Price Optimization

Will be updated with all project.

Data Science Full Tutorial beginner to advanced

Will be updated with strong github repo.

Interviews

Will be supported real interview home tasks.
What I do?

Problems I like solving.

Software Engineering

Across the stack, including responsive web development

Infrastructure Planning

Platform planning, from failover, redundancy, high availability, and extreme TPS environments

Solutions Architecting

Gathering business requirements and translating that into written technical specifications

Presentation Skills

Excellent communication and presentation skills in front of large and medium sized crowds, from developers to the C-suite

Containerization (Docker & K8S)

Deep experience in containers and container orchestration platforms like Docker and Kubernetes (K8S)

Cloud Services

AWS Certified, GCP, Azure, DigitalOcean, and more. Talk to me about everything serverless.

My Specialty

Let's get specific

Python Programming

Machine Learning (Sk-Learn, SciPy, TensorFlow)

Databases (SQL & NoSQL)

Data Analysis (Pandas, Numpy, Seaborn) - Feature Eng

Deployment (Docker, Flask, FastAPI)

Cloud Tech - GCP (Google Cloud Platform)

Big Data (ETL, PySpark, Elasticsearch, Kafka, Hadoop)

Statistical Analysis (Hyphothesis Testing, A/B Testing)

Education

Education

Fırat University
Fırat University 09/2014 - 06/2019 Bachelor of Computer Science (BsCs)
  • Major in Computer Science and Software Engineering
Experience

Work Experience

Data Science Engineer

DeFacto

Sep 2021 - Current
  • Enhanced a prediction model using Linear Regression to estimate stock values with region sales history for new stores, and improved the model success by XGBoost.
  • Created new 375 clothing combinations to increase sales 15% by analyzing data and creating K-Means Clustering model on Google Cloud Platform and Python.
  • Developed an ETL pipeline to extract data from HDFS/Local DB/GCP and clean, merge data, segment costumer to 120 types and load to Elastic Search Cluster and Kafka CRM integration system using PySpark in JupyterHub.

Machine Learning Engineer

Zack.AI

Jan 2021 - Aug 2021
  • Promoted accuracy 20% more than the historical average to forecast weekly sales of 10,000 products, using product characteristics with Fine-Tuning XGBoost model.
  • Decreased CRF-based interactive NLP chatbot’s response time from 10+ seconds to under 3 seconds by rewriting code with best practices using Python.
  • Applied Bert transformer ML technique to develop auto labeling NLP model accuracy from %65 to %85+ using TensorFlow in Python.

Data Scientist

DeepSearch Analytics

Jul 2020 - Dec 2020 (Contract)
  • Performed various data visualization, data cleaning, and feature selection on 1 TB text by Pandas and NLTK packages by defining patterns using Python on PyCharm.
  • Produced statistical modelings such as Text Analytics, social network analysis, and Natural Language Processing on 7 GB CSV data using Python.

Data Scientist

IndiaNIC Infotech Ltd

Jan 2020 - June 2020 (Pandemi)
  • Applied Light GBM method to decrease MAPE from 10% to under 5% forDemand Forecasting using Machine Learning with Python.
  • Improved F1 Score to >0.9 by feature selecting and Naive Bayes instead of Linear Regression for sentiment analysis on 20 GB of unstructured data.
  • Collaborated with an agile team to implement the ETL and optimized 575 SQL queries to perform data extraction.

Jr. Data Scientist

Boraq Group Ltd

Jul 2018 - Dec 2019
  • Saved 5x2 daily source by developing a collaborative product to split daily action data to the BA team using SQL and Python.
  • Performed sentiment analysis to surface reviews most likely to be relevant to a given user to increase sales by 6% using Pandas and Scikit-Learn on Python.
  • Improved Company Secretary coaching and 26% fewer customer complaints.
Read

Recent Blog

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