Aiden Ahmet Erdogan

Berufserfahrung von Aiden Ahmet Erdogan

• Bis heute 1 Jahr und 5 Monate, seit Jan. 2023

  Data Scientist

  CRED

  - Industry generation system developed with PEFT LLM Llama & GCP, resulting in over 10% accuracy increase in ML matching models, reducing errors by 15%. - Operational efficiency boosted with 3 h/week saved in deployment time and 2 h/week in team collaboration through streamlined deployment processes and automated predictions in Slack. - Achieved a 35% ($32+K) reduction in monthly cloud expenditure via strategic optimization of virtual machines, ML models, and storage utilization.

• 1 Jahr und 4 Monate, Sep. 2021 - Dez. 2022

  Data Scientist

  DEFACTO GmbH

  - Enhanced sales prediction models, reducing errors by 10% through algorithm optimization, resulting in a $150K quarterly revenue boost. - Introduced dress combination recommendation system, driving a 5% sales increase, utilizing the Clustering method on AWS. - Developed a targeted customer segmentation model with 120 types, leading to a 30% campaign response rate rise. - Implemented Neural Machine Translation system for DeFacto websites, achieving a 95% accuracy boost, saving over $5K monthly.

• 8 Monate, Jan. 2021 - Aug. 2021

  Data Scientist

  Zack AI

  - Secured $300 investment from foundations by optimizing chatbot multipurpose, introducing dialog engine, & real-time analysis dashboard, resulting in 20% higher engagement & 15% lower support costs. - Reduced CRF-based NLP chatbot's response time from 10+ seconds to under 3 seconds by Java to Python transition & algorithm updates. - Improved BERT NLP auto-labeling model, achieving an 85% acc. increase with TensorFlow, cutting labeling errors by 25%, saving 5 h/w, & optimizing workflows for cost efficiency.

• 1 Jahr, Jan. 2020 - Dez. 2020

  Data Scientist

  IndiaNIC

  - Reduced MAPE to <10% for Demand Forecasting, utilizing data cleansing, advanced feature engineering, and Light GBM with Linear Regression, resulting in 10% fewer stockouts and 5% less excess inventory. - Achieved F1 Score >0.9 in sentiment analysis on a 20 GB dataset, leading to 15% higher customer satisfaction and engagement via meticulous feature selection and Naive Bayes integration. - Collaborated on ETL execution and optimized 575 SQL queries for data extraction in an agile environment.

• 1 Jahr und 6 Monate, Juli 2018 - Dez. 2019

  Data Scientist

  Boraq Group

  • Optimized data workflow, saving 10 weekly hours by creating a collaborative tool to split action data for the BA team, utilizing SQL and Python. • Performed data scraping from Twitter and sentiment analysis model in Python using Pandas and Scikit-Learn, pinpointing reviews relevant to users and yielding a 6% boost in sales. • Enhanced Company Secretary coaching, leading to a 26% reduction in customer complaints.