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AI Architect

Infosys -
Blue Ash, OH

Quick Apply

Job Details

Qualifications

AI models
Data quality checks
AI use case identification
Predictive modeling analysis
SAS
Technical documentation
Data quality assurance
R
AI tools proficiency
SAS language
Quality improvement leadership
White papers
Quality performance measurement
Outlier detection
Content creation
Model deployment
Data quality monitoring
Mentoring
Instructor-led training (training delivery method)
Prototype creation
Improving predictive model accuracy
Leading team collaboration initiatives
Scalability
Data-driven problem-solving
Model training
Business planning
Predictive analytics projects
Implementing machine learning algorithms
Test analysis
Senior level

Full Job Description

In the assigned Job Role of Data Science Consultant 3, your Area Of Responsibility will be as below:

Review data preparation tasks, and plans to address patterns or anomalies, while ensuring data readiness for advanced modeling and AI.
Review models for complex use cases (e.g., forecasting models, LLM-based solutions), and refine algorithms to meet business needs.
Review plan for smooth deployment into scalable, production-ready solutions.
Review test plans and test results for analytics use cases, while defining optimization standards for model accuracy and stability, in alignment with business goals.
Build models and analytics solutions tailored to business needs.
Ensure quality and scalability across client engagements while actively contributing to knowledge assets and innovation streams.
Leverage tools like SAS and R/Python to create reusable customizations for non-ML, ML, and deep learning algorithms, while enhancing analytics including LLMs, and create innovative, cost-effective solutions.
Review and refine analytics problems; identify data sources and extract from diverse environments.
Oversee analysis execution and drive business insights.
Create monitoring strategies across multiple projects, embedding governance frameworks to ensure robustness, reliability, and risk awareness.
Review monitoring frameworks, refine documentation/reporting templates, and present insights on anomalies or slippages to stakeholders.
Refine documentation strategy across teams, ensuring transparency and reproducibility of complex analytics solutions.
Collaborate with cross-functional teams, ensuring alignment between analytics delivery and business strategy.
Review analytics outputs for adherence to quality frameworks and project commitments.
Recommend improvements to quality metrics and guide team members to align with standards.
Identify and recommend model changes needed for successful deployment.
Engage in creation and refinement of IP assets such as analytics prototypes and accelerators.
Develop insights, whitepapers, and proof-of-concept summaries that highlight innovative thinking.
Review innovative models and applications in non-ML, ML, deep learning, or LLM areas.
Support participation in forums and internal knowledge exchanges.
Deliver training sessions on technical and analytics-specific topics.
Collaborate on content creation and mentor team members through hands- on guidance in live projects.
Provide input for segment and unit-level business plans.

Your contribution to the team:

A strong focus on innovation and scalable analytics solutions.
Proactive problem-solving ability for complex, data-driven business challenges.
Deep technical expertise across advanced modeling and AI use cases.
A strategic mindset to align analytics with business goals.
Ability to mentor team members and drive continuous improvement.
Strong communication and knowledge-sharing capabilities.

Quick Apply

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Scientist II

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Research Associate

AI Engineer

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