AI/ML Technical and Functional Analyst with Business Analysis

Candidate current location should be in NJ/NY with NY/NJ local enterprise projects in recent

Required Skills

• Minimum 10 years of experience in functional and technical analysis across enterprise applications and data-driven solutions.
• Minimum 5 years of strong understanding of AI/ML concepts, automation frameworks, and data fundamentals.
• Minimum 10 years of experience preparing BRDs, FSDs, user stories, workflow diagrams, and system documentation.
• Minimum 7 years of experience analyzing structured and unstructured data and interpreting results to support business decisions.
• Minimum 7 years of hands-on experience writing complex SQL, optimizing queries, and working with enterprise RDBMS platforms (e.g., SQL Server, Oracle, PostgreSQL).
• Minimum 5 years of experience working with enterprise data warehouses, ETL/ELT processes, and data modeling.
• Minimum 5 years of experience applying statistics and ML techniques on real-world datasets, including model validation and iteration.
• Minimum 5 years of exposure with data libraries (e.g., Python, pandas) and exposure to CI/CD or MLOps practices.
• Minimum 5 years of experience evaluating AI tools, frameworks, or vendors and making solution or architecture recommendations.
• Minimum 7 years of experience leading or overseeing pilots/POCs, defining success metrics, and contributing to scale-up or roadmap planning.

Description:

Tasks & Duties:

• Lead workshops with business stakeholders to document business processes, pain points, user stories, functional specifications, and acceptance criteria.
• Perform feasibility analysis to identify opportunities for AI/ML, automation, decisioning, and workflow optimization.
• Develop process maps (BPMN), system flows, data lineage, and integration documentation.
• Translate business requirements into clear, actionable technical specifications, including APIs, data flows, validation rules, and model inputs/outputs.
• Analyze existing applications, databases, integrations, and AWS cloud environments to inform solution design and implementation.
• Collaborate closely with architects, developers, data scientists, and engineers to ensure accurate interpretation of requirements and solution intent.
• Work with data science and engineering teams to define data needs, metrics, business rules, validation logic, and AI/ML model behavior.