Operational Management

• Oversee daily operations across multiple teams handling data analysis, reporting, quality control, business process analysis, and AI initiatives.

• Ensure adherence to delivery timelines, SLAs, and quality standards for recurring production outputs and ad hoc requests.

• Monitor workload distribution, capacity utilization, and pipeline health across teams.

• Escalate delivery risks, data quality issues, or resourcing constraints with clear mitigation plans.

Delivery & Quality Governance

• Enforce quality control standards for incoming and outgoing test files, production outputs, and reporting artifacts.

• Drive consistency in MIS, reporting cadence, and metrics definitions across teams.

• Ensure process documentation, handoffs, and audit trails are maintained and followed.

• Partner with leads and senior contributors to improve process efficiency, data management, and AI opportunities identified by the teams.

People Leadership

• Provide day-to-day supervision, coaching, and performance management for analysts, specialists, and engineers.

• Set clear expectations on role responsibilities, priorities, and deliverables.

• Support onboarding, skill development, and role progression in collaboration with functional leads.

• Foster a culture of accountability, continuous improvement, and collaboration across teams.

Stakeholder & Cross‑Functional Collaboration

• Act as primary operational point of contact for internal stakeholders, consultants, and partner teams.

• Translate business requirements into actionable work plans for technical teams.

• Align team execution with broader consulting, analytics, and product delivery objectives.

• Support leadership with status reporting, operational insights, and issue analysis.

Digital Excellence and Optimization

• Identify patterns impacting efficiency, quality, or delivery predictability.

• Promote standardization of workflows, reporting templates, and operational practices where applicable.

• Support implementation of new tools, reporting methods, and governance processes introduced by leadership.

• Oversee AI deployment and integration (Agentic, AI Models, off-the-shelf), ensuring alignment with business goals and collaboration across teams to drive effective implementation and ongoing optimization.

Required Qualifications

• Bachelor’s degree in Business, Statistics, Mathematics, Finance, Data Science, Computer Science, Computer Engineering, or a related field.

• 3–5 years of relevant industry experience in analytics, data operations, AI, or consulting environments.

• Prior experience leading or supervising technical or analytical teams.

• Strong understanding of:

  • Data analysis and reporting workflows

  • Quality control and data hygiene practices

  • Business process analysis and operational metrics

• Proficient in Microsoft Office, especially Excel; familiarity with Power BI, SQL, or similar tools is an advantage.

• Strong communication skills with the ability to engage both technical and non‑technical stakeholders.

• Demonstrated ability to manage multiple priorities and deliver under tight timelines.

• Ability to quickly learn and apply enterprise AI tools and technologies to support technical workflows and business objectives

Preferred Qualifications

• Exposure to AI (Agentic, AI Models, off-the-shelf), workflow optimization, or analytics consulting environments.

• Experience supporting teams with mixed skill profiles (analysts, engineers, specialists).

• Comfortable operating in a matrixed environment with multiple stakeholders.

• Detail-oriented with a strong bias toward execution and follow‑through.

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