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We are seeking a highly motivated and technically skilled professional to join the Analytics Solutions Integration team within Credit Analytics. This position is ideal for professionals excited about implementing predictive models for multiple business functions, modernizing legacy processes, and applying advanced technologies to transform analytics delivery.

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As an Analytics Scientist, you will bridge the gap between analytical model development and production deployment, using SAS, Vendor tools on OnPrem and Cloud based applications. You will also be a key contributor in modernizing legacy mainframe-based batch testing processes through automation, dataset comparison frameworks, and summarization/reporting of the data.

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Responsibilities:

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Implement, validate, test, and Productionalize the predictive models and risk strategies across global platforms. Collaborate with Data Scientists, Business teams, and IT to ensure smooth transition of models from development to production. Design and implement automated pipelines that support batch testing workflows involving mainframe JCL, flat files, VSAM or legacy datasets. Develop reusable and repeatable automation for comparing and summarizing data between legacy and modernized systems for multiple business functions. Use GCP services such as BigQuery, PostgreSQL, Cloud Functions, Cloud Storage, Cloud Composer, Cloud Run, and Pub/Sub to build scalable workflows that support analytics delivery. Move mainframe outputs to cloud storage for processing and use SQL/Python/LLM-enhanced logic to analyze results. Identify opportunities to introduce automation, GenAI tooling, and workflow simplification and develop the Proof-of-Concepts to enhance delivery processes through automation. Provide data analysis, SQL/SAS/Python programming, and on-demand reporting aligned to business needs.

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Qualifications:

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Bachelor’s degree in computer science, Data Science, Information Systems, Engineering, or related field. 4–5 years of programming experience in object-oriented and procedural paradigms (Example: Java, SQL, and Python),  with experience preferably in Statistical Analysis System software (like"SAS RealTime Decision Manager"). Experience with Relational Database Management Systems (like DB2) 1–2 years hands-on experience with Google Cloud Platform (GCP) including BigQuery, PostgreSQL, Cloud Storage, Cloud Functions, etc. Familiarity with Waterfall, Agile, and PDO methodologies. Experience working with IT testing environments, regression testing, and automated validation. Strong understanding of modern automation frameworks and AI-powered tooling like Agentic AI.

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Even better you’ll have:

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Master’s degree. Experience integrating or automating processes involving mainframe legacy systems. Gen AI tooling - Agentic AI, Workflows & Cloud integration.

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XML job scraping automation by YubHub

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