Consultant, Process Excellence-PE

About the Role

The Consultant – Process Excellence contributes to FP&A transformation engagements, bringing structured process analysis skills, hands-on AI and automation tooling experience, and growing domain knowledge across processes and industry.

Key Responsibilities

• Conduct As-Is process maturity assessment (L1–L4) and structured gap analysis across Finance sub-processes.
• AI-Ready Process Analysis: Analyze FP&A workflows to identify automation and AI intervention opportunities.
• Python (must have): Write clean functional scripts for data extraction, transformation, API calls, and workflow automation tasks; independently run and debug scripts within Finance transformation contexts.
• SQL (must have): Query Finance datasets from ERP / data warehouse environments; perform joins, aggregations, and sub-queries to extract operational insights supporting process assessments.
• Hands-On AI Tooling: Apply at least one of – GenAI prompt engineering, RPA scripting, process mining tools, or LLM-based workflow prototyping – to real Finance process challenges.
• Data Analysis & Finance Reporting: Build analytical outputs using Excel, Power BI, Python, or SQL; support delivery of process performance dashboards and KPI tracking frameworks.
• Solution Documentation & Delivery Contribution: Prepare workshop materials, process deliverables, status reports, and presentation decks; contribute to business case quantification.
• Finance Sub-Process Knowledge: Actively developing FP&A processes in depth over time.
• Collaborate with AI/data engineers and automation specialists to embed technology interventions into redesigned process flows.

Requirements & Tech Stack

Must-Have Skills

• Financial Planning & Analysis Transformation – process analysis, AI enabled design and improvements, Identifying / mapping AI/automation opportunity for planning process productivity improvements.
• Python
• SQL

Good-to-Have Skills

• Familiarity with AI/ML-powered forecasting techniques — predictive analytics, anomaly detection, scenario modelling, and rolling forecast automation; exposure to tools such as Azure ML, Amazon Forecast, or embedded AI capabilities within EPM platforms.
• Basic understanding of Multi-agent AI frameworks (LangChain / CrewAI / AutoGen) and their applicability to FP&A automation use cases such as variance commentary, narrative generation, and report drafting.
• Hands-on exposure to one or more EPM/CPM planning platforms (Anaplan, Oracle EPM Cloud, Workday Adaptive, SAP BPC/Analytics Cloud) for budgeting, forecasting, and driver-based modelling.
• Working knowledge of FP&A processes and terminology for at least one industry vertical — including planning cycles, forecast cadence, and management reporting structures.

Qualifications

• CA / CPA / MBA Finance / B.Tech / B.E / Bachelors in Data Science — Tier 1 institute.