Data Scientist Analyst

he Spec Analytics Intmd Analyst is a developing professional role. Deals with most problems independently and has some latitude to solve complex problems. Integrates in-depth specialty area knowledge with a solid understanding of industry standards and practices. Good understanding of how the team and area integrate with others in accomplishing the objectives of the sub function/ job family. Applies analytical thinking and knowledge of data analysis tools and methodologies. Requires attention to detail when making judgments and recommendations based on the analysis of factual information. Typically deals with variable issues with potentially broader business impact. Applies professional judgment when interpreting data and results. Breaks down information in a systematic and communicable manner. Developed communication and diplomacy skills are required in order to exchange potentially complex/sensitive information. Moderate but direct impact through close contact with the businesses' core activities. Quality and timeliness of service provided will affect the effectiveness of own team and other closely related teams.

Responsibilities:

• Model Development: Assist in the development, fine-tuning, and deployment of Machine Learning and Deep Learning models. Fine tune large language models or build internal SLMs from scratch.
• Gen AI / Agentic AI : Contribute to Design and Develop of POCs / full scale solutions on various automations in Operations including Conversational AI, Muti Agent Systems, real time evaluation for multiple services.
• Data Pipelines: Implement and maintain AI pipelines and infrastructure to support model training and deployment.
• RAG Frameworks : Customize and fine-tune existing / new RAG frameworks to meet project requirements.
• Research and Experimentation: Conduct research to advance the state-of-the art in generative modeling and stay up to date with latest advancements in the field.
• Performance Optimization: Optimize and fine-tune models for performance, scalability, and robustness
• Collaborative Projects: Work with cross-functional teams to integrate AI models into various applications and services.
• MRM Documentation: Maintain clear and comprehensive documentation of model architectures, processes, and findings
• Strong understanding of Model Risk Management (MRM) and Fair Lending (FL) guidelines for LLM based solutions
• Present findings and project progress to stakeholders and management.

Qualifications:

• 5+ years relevant experience with AIML Projects
• Experience with developing & deploying machine learning models in a production environment.
• Familiarity with MLOps practices and tools.
• Possess analytic ability and problem solving skills
• Working experience in a quantitative field
• Willing to learn and can-do attitude
• Excellent communication and interpersonal skills, be organized, detail oriented, flexible and adaptive to matrix work environment
• Ability to build partnerships with cross-function leaders

Education:

• Bachelors/University degree or equivalent experience

This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.

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Job Family Group:

Decision Management

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Job Family:

Specialized Analytics (Data Science/Computational Statistics)

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Time Type:

Full time

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Most Relevant Skills

Please see the requirements listed above.

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Other Relevant Skills

For complementary skills, please see above and/or contact the recruiter.

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