About

Yash Mahendra is a highly skilled and experienced Quantitative Technologist at qube research & technologies with over 3 years of relevant experience. He is a problem solver with a competitive programming background and a keen interest in developing new features in software after researching the underlying technologies and concepts. Yash has worked extensively with Java and Python with corresponding frameworks. He is currently playing with data at scale and has worked on real-time credit underwriting service design and implementation at bright money. He has also designed and implemented an end-to-end service of account aggregation as 16 various microservices to support fetching financial data in real-time and batch fashion. Yash has experience in unifying data schemas along with monitoring data validation, data quality degradation, data recency, and missing data computation. He has developed scalable refresh pipelines for keeping 0.5M accounts up to date in a short period using Airflow jobs and developed AWS Glue Jobs (PySpark) for providing data to various other services via S3. He has also integrated in-depth with aggregators such as Plaid, Fiserv, Capital One Direct Integration, and Finicity. Yash has experience in database and query-plans tuning for large tables with 300M records. He has mentored, performed code reviews, project planning and provided historical context in a team of 6. He has also developed dashboarding and alerting for business metrics, adding features for fast CS tickets resolution and stakeholders. Yash has a PG Diploma in Data Sciences, Machine Learning, and Big Data from iiit Bangalore and a Bachelor of Technology in Computer Science from VIT. He is currently pursuing a Master of Science in Machine Learning and Artificial Intelligence from Liverpool John Moores University, which is expected to be completed in 2022. Yash has a strong tech stack that includes Research Scientist, AWS, Apache Airflow, Python, Integration, Software Engineer, Data Engineering, Django, AWS Glue, Spark, RabbitMQ, Kafka, Jenkins, Microservices, Web, Recommendation system, Java, and ML.