GenAI & ML Scientist for High-Impact E‑Commerce

StartupHeroes; Turkey; On-site; TRY 300,000 - 520,000; Full time

Job summary

StartupHeroes is looking for a Data Scientist to join a diverse, collaborative team. The role focuses on delivering AI-driven features for our e-commerce platform, from data prep and feature engineering to deploying and monitoring models.

You will work closely with product, engineering, and operations to improve analytics, recommendations, and experimentation. You will ship GenAI projects, fine-tune models, and contribute to scalable, production-grade systems in an Agile environment.

Qualifications

• 3+ years of hands-on experience delivering end-to-end ML in production.
• Deep understanding of data preprocessing, feature engineering, modeling, and evaluation.
• Advanced Python proficiency for production-grade code.
• Experience deploying AI features in e-commerce or ops domains is a plus.

Responsibilities

• Collaborate with cross-functional teams to design, build, and deploy AI-driven features for the e-commerce platform.
• Develop and ship GenAI projects and intelligent agents.
• Own end-to-end DS workflow from data prep to deployment and monitoring.
• Define and maintain best practices for model monitoring and retraining.
• Work with product, engineering, and ops teams to optimize user experience via analytics and experimentation.
• Participate in Agile/Scrum ceremonies and code reviews.

Skills

Hands-on ML

Python programming

Agile/Scrum

Feature engineering

Model evaluation

Team collaboration

Education

Bachelor's degree in CS/Engineering/Data Science

Tools

Docker

Job description

StartupHeroes is looking for a Data Scientist to join a diverse, collaborative team. The role focuses on delivering AI-driven features for our e-commerce platform, from data prep and feature engineering to deploying and monitoring models.

You will work closely with product, engineering, and operations to improve analytics, recommendations, and experimentation. You will ship GenAI projects, fine-tune models, and contribute to scalable, production-grade systems in an Agile environment.