Summary
Enes Öztürk is a Mid Data Scientist with 9 years of experience building production ML systems, credit risk models, and LLM-powered assistants that serve millions of users. He has designed and deployed scoring pipelines (Risk, RFM, Value Segment) and performed rigorous model validation and stability testing to ensure long-term robustness. Enes combines hands-on data engineering—Airflow orchestration, MySQL/ElasticSearch optimization, Dockerized microservices, and GitLab CI/CD—with model fine-tuning techniques like LoRA and tokenizer customization for domain-tuned LLMs. He emphasizes observability and operational reliability using Grafana, Kibana, and the Elastic Stack to turn ML outputs into actionable business insights. Based in Tampere and originally from Turkey, he blends consultancy experience and academic work with practical production deployments across fintech and enterprise contexts. Notably, he has repeatedly delivered AI assistants and analytic tools that directly improve customer engagement and financial decisioning at scale.
9 years of coding experience
4 years of employment as a software developer
Bachelor's degree Computer Engineering, Bachelor's degree Computer Engineering at Bülent Ecevit University
English