Senior Technical & Functional Analyst; AI​/Automation

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, Postgre
  
  SQL).
• 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.

• 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.
• Lead and support AI pilots and POCs, including defining success metrics, tracking outcomes, and documenting lessons learned for scale‑up.
• Conduct root cause analysis and recommend improvements to accuracy, efficiency, compliance, and user experience.
• Support dashboarding, analytics KPIs, and reporting for business and executive leadership.
• Support User Acceptance Testing (UAT), traceability, defect triage, and business sign‑offs.
• Partner with QA teams to ensure robust testing coverage across multiple business and edge scenarios, especially for AI‑driven solutions.
• Act as a liaison between business program areas, IT delivery teams, vendor partners, and technical SMEs to ensure alignment and clarity.
• Produce regular status updates, technical documentation, and executive‑level summaries on progress and outcomes.
• Support training, SOP updates, knowledge transfer, and production rollouts.