AR-GE Mühendisi

Yapı Kredi

Qualifications:

• Having / Pursuing or willing to have an M.Sc. or Ph. D. degree in Machine Learning/Deep Learning related field from Computer, Industrial or Electrical and Electronics Engineering
• Proficiency in coding with Python or any other scientific programming language (R, Julia, Matlab)
• Hands on experience with common frameworks (pandas, numpy, matplotlib) and common ML frameworks (scipy, scikit-learn, or their equivalents in other languages)
• Experience in NoSQL databases (Redis, MongoDB, Cassandra, etc)
• Strong understanding of ML training, testing, data processing steps and ML project pipelines,
• Eager to follow technical literature and willing to contribute actively by publishing academic papers in international conferences
• Strong understanding of object-oriented design and programming, (Java, C++ etc.),
• Experience in developing data processing tasks using pySpark such as reading data from sources in different format, merging data with complex conditions, performing data enrichment/transformations
• Experience in implementing with Big Data Technologies, like Airflow, MapReduce, Pig, Hive, Kafka, Sqoop, and Flume
• Experience in Linux/Unix operating system
• Experience in building web services (REST, SOAP)
• Experience with enterprise Java technologies (Spring, Maven, Hibernate etc.)
• Experience in containerization and orchestration tools (Docker, Kubernetes, etc.)

Job Description

We are seeking to hire talented R&D Engineers to join our Applied Data Science team in Applied AI and R&D department who have a passion for solving real world problems in particular, credit risk, financial risk management and fraud detection

• You will be working closely with other fast-paced and highly-skilled R&D engineers in a pro-active and R&D oriented software development team to take ML models from R&D to production, scale and maintain them
• As a full-stack R&D Engineer, you will take a role in each phase of the project, i.e. data analysis, technical design, prototyping, ML development, integration development to core banking systems and end-to-end testing