Sr. Financial Planning and Analysis Analyst
KLDiscovery is looking for someone who can build the infrastructure, run the models, develop strategy. This person will sit at the intersection of financial systems, data engineering, advanced modeling, and strategic insight, and they will operate with significant autonomy.
We are a $350M PE-backed company going through a Quality of Earnings process. The Finance function is rebuilding from the ground up: new planning platform (Pigment), new India data team, new AI agent infrastructure, new KPI framework. This role will be a founding architect of that rebuild, not a passenger in it.
On any given week you might build a Python script to automate a data pipeline, develop a 3+9 reforecast in Pigment, write a one-page strategy memo on the financial impact of a pricing change, and co-build a Claude AI agent with the US Sr. FP&A Analyst.
Key Responsibilities:
Financial systems and data infrastructure
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Design and build Oracle → Pigment data pipelines that are clean, automated, and reconciled daily.
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Own data integrity across Oracle, Pigment, and Salesforce; catch discrepancies before the US team's morning.
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Automate manual report pulls (SSRS AR reports, collections reports, close checklists).
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Pigment/Adaptive administration: versioning, data refresh, user access, API connections.
AI agent co-development (with US Sr. FP&A Analyst)
- Co-build all six Claude agents: Close, Rolling Forecast, Variance+Commentary, Strategy+Scenario, Investor Reporting, Collections Intelligence.
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Own the data feeds each agent reads; if the data is wrong, the agent is wrong.
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Once agents are live: operate, monitor, validate outputs, and continuously improve prompt quality and accuracy.
Financial modeling and analysis
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Rolling forecast: end-to-end ownership of actuals ingest, model update, reforecast, sensitivity, and assumptions memo.
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EBITDA Bridge: monthly production from June 2026 with waterfall, variance commentary, and distribution to the CFO.
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3+9 reforecast: monthly update of full-year forecast, refreshed assumptions, drift flagged, distributed to ELT.
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Scenario modeling: acquisition, pricing change, headcount, DSO improvement; P&L impact plus sensitivity range.
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Capital and investment analysis: ROI modeling for major decisions (India build, Pigment, BI tooling, and other infrastructure replacements).
Strategy development and original insight
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Peer benchmarking: quarterly comparison of KLD vs. PE-backed peers at $300M+ on close cycle, DSO, EBITDA margin, and headcount ratio.
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Strategy memos: one-page financial impact write-ups for key decisions, written to go directly to the CFO and ELT as-is.
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KPI framework: define scorecards by group (Collections, Analysts, FP&A, Sales Ops) with baseline, target, and measurement.
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Identify patterns in the data the US team hasn't seen, and surface them unprompted.
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ELT pre-reads: financial analysis, scenario tables, and recommendation summaries for executive meetings.
Qualifications
Financial Modeling:
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Four to six years building integrated three-statement models in FP&A, consulting, banking, or PE; must be able to build from a blank sheet.
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Expert Excel across dynamic models with scenario toggles, sensitivity tables, named ranges, and zero hardcoded assumptions.
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Experience building PE-grade deliverables (EBITDA bridges, rolling forecasts, investor packages, scenario memos) in live contexts.
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Pigment, Adaptive, Anaplan, or similar is non-negotiable; you will administer the platform from day one.
Technical Systems:
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Python (pandas, requests, API calls) to build and maintain data pipelines without IT assistance.
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SQL to query Oracle at GL level, validate data, and build reconciliation logic.
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REST API experience reading and writing via API (Pigment API and Claude API).
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LLM API familiarity with the ability to co-build AI agents, write system prompts, and validate outputs.
Strategy and insight:
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Ability to tran