Implementation of a new service at Google Cloud Platform (GCP). Service a long term strategic solution for the bank providing a processing (BigData) of european payments data for the purpose of data analysis, data science, product management decisions, AML, storage, archiving and KYC processes. Mass Payment Data & Cloud processing platform using the latest technology stack and integrated Google tools. Interesting set of surrounding interfaces using different integration layers and protocols (API, SAPI, PubSub, BQ ingestions, Juniper ingress, egress, ConnectDirect, IBM MQ etc) as the consolidation of the orchestration layer achieving the sustainable quality and outcome.
- Build Machine Learning (ML) models on Payments data for various use cases.
- Explain model results to stakeholders.
- Explore Payments data for ML use case identification.
- Data Analytics.
- Analyze / Review requirements, prepare the design document, system / solution proposal document and system test plans.
- Execute project specific development or configuration and maintenance activities in accordance to applicable standards and quality parameters.
- Setting up the right environment for projects.
- Ensure delivery within schedule by adhering to the engineering and quality standards.
- Own & deliver end to end projects of Payment Data Platform.
- Able to work under pressure on deliverables, violations and incidents.
- Provide Weekly & Monthly Project Updates to stake holders & Management.
Who we're looking for?
- Experienced in Machine Learning (ML) modelling techniques like NLP, time series, Recommender systems, Neural nets etc.
- Experienced in building production ML applications.
- Experienced in data engineering (Hadoop, Data proc, Spark, etc.)
- Python, SQL, Google Cloud Platform (GCP) knowledge/experience.
- Experienced with relational databases like Oracle, MSSQL, Big Query etc.
- Reporting tools like Tableau, Data studio, etc.
- CI / CD for model deployment.
- Comfortable with Unix/Linux.
- As per Agile development methodology should be flexible to support developed code in production environment.
- Knowledge on GCP Data services preferred.
- Working experience in a managing a large database.
- Existing hands on experience in the field of large data/mass data processing.