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Skills and competencies:
Required:
· Strong analytical skills in conducting sophisticated statistical analysis using bureau/vendor data, customer performance
Data and macro-economic data to solve business problems.
· Working experience in languages PySpark & Scala to develop code to validate and implement models and codes in
Credit Risk/Banking
· Experience with distributed systems such as Hadoop/MapReduce, Spark, streaming data processing, cloud architecture.
- Familiarity with machine learning frameworks and libraries (like scikit-learn, SparkML, tensorflow, pytorch etc.
- Experience in systems integration, web services, batch processing
- Experience in migrating codes to PySpark/Scala is big Plus
- The ability to act as liaison conveying information needs of the business to IT and data constraints to the business
applies equal conveyance regarding business strategy and IT strategy, business processes and work flow
· Flexibility in approach and thought process
· Attitude to learn and comprehend the periodical changes in the regulatory requirement as per FED


- Hands-on development and optimization of image enhancing algorithms for image processing using computational imaging
- Working with peer teams on researching and resolving complex software and system problems
- Analvze and optimize different methodologies to improve output of image processing
- Work closely with Quality Assurance teams to refine algorithms for optimal system performance
- Support products from the early development and prototyping phases through to production
- Developing functional specifications per customer requirements
- Good understanding of image processing techniques such as edge detection skills, image alignment, removing noise, image segmentation, correction/modification, compression, and image reconstruction
- Experience using AWS (that’s just common sense)
- Experience designing and building web environments on AWS, which includes working with services like EC2, ELB, RDS, and S3
- Experience building and maintaining cloud-native applications
- A solid background in Linux/Unix and Windows server system administration
- Experience using https://www.simplilearn.com/tutorials/devops-tutorial/devops-tools" target="_blank">DevOps tools in a cloud environment, such as Ansible, Artifactory, https://www.simplilearn.com/tutorials/docker-tutorial/what-is-docker-container" target="_blank">Docker, GitHub, https://www.simplilearn.com/tutorials/jenkins-tutorial/what-is-jenkins" target="_blank">Jenkins, https://www.simplilearn.com/tutorials/kubernetes-tutorial/what-is-kubernetes" target="_blank">Kubernetes, Maven, and Sonar Qube
- Experience installing and configuring different application servers such as JBoss, Tomcat, and WebLogic
- Experience using monitoring solutions like CloudWatch, ELK Stack, and Prometheus
- An understanding of writing Infrastructure-as-Code (IaC), using tools like CloudFormation or Terraform
- Knowledge of one or more of the most-used programming languages available for today’s cloud computing (i.e., SQL data, XML data, R math, Clojure math, Haskell functional, Erlang functional, Python procedural, and Go procedural languages)
- Experience in troubleshooting distributed systems
- Proficiency in script development and scripting languages
- The ability to be a team player
- The ability and skill to train other people in procedural and technical topics
- Strong communication and collaboration skills
As a special aside, an AWS engineer who works in DevOps should also have experience with:
- The theory, concepts, and real-world application of Continuous Delivery (CD), which requires familiarity with tools like AWS CodeBuild, AWS CodeDeploy, and AWS CodePipeline
- An understanding of automation