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Tier-1 brand, metro location, and mid-level generalist automation/data skillset increase applicant competition.
Core Python, data and automation skills are transferable, but finance controls and Dataiku preference increase domain specificity.
Explicit 3-5 years requirement plus mandatory Python, Dataiku, AI and financial controls make filters strict.
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Own end-to-end delivery of Python-led automation solutions including design, build, testing, and production support within the Morgan Stanley at Work Agility & Strategic Intelligence team.
Translate manual business processes into automation-ready process maps, user stories, and test scenarios, applying AI and low-code/no-code tools to improve operational efficiency with control.
Collaborate with business, onshore/offshore tech teams for requirements gathering, status updates, and continuous process improvement including validation of AI outputs and maintenance of control documentation.
3-5 years professional experience in Python scripting, data automation, or software development with hands-on project delivery.
Bachelor’s degree in Computer Science, IT, Software Engineering, or equivalent experience in related disciplines.
Strong hands-on Python skills including scripting, data processing, API integration, validation, and troubleshooting.
Basic AI/GenAI knowledge including LLM understanding, prompt engineering, responsible AI use, and use of AI-assisted developer tools like GitHub Copilot.
Experienced in delivering practical automation solutions independently within Agile/SDLC environments for well-defined workstreams at associate level.
Comfortable using and integrating low-code/no-code platforms, AI tools, and data workflow solutions such as Dataiku, with ability to design processes and validate outputs.
Capable of interfacing effectively across technical and non-technical stakeholders, coordinating multi-location teams and owning delivery of clear documentation, testing, and production support.