About the role
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
Design and build Oracle → Pigment data pipelines that are clean, automated, and reconciled daily.
Own data integrity across Oracle, Pigment, and Salesforce; catch discrepancies before the US team's morning.
Automate manual report pulls (SSRS AR reports, collections reports, close checklists).
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.
Own the data feeds each agent reads; if the data is wrong, the agent is wrong.
Once agents are live: operate, monitor, validate outputs, and continuously improve prompt quality and accuracy.
Financial modeling and analysis
Rolling forecast: end-to-end ownership of actuals ingest, model update, reforecast, sensitivity, and assumptions memo.
EBITDA Bridge: monthly production from June 2026 with waterfall, variance commentary, and distribution to the CFO.
3+9 reforecast: monthly update of full-year forecast, refreshed assumptions, drift flagged, distributed to ELT.
Scenario modeling: acquisition, pricing change, headcount, DSO improvement; P&L impact plus sensitivity range.
Capital and investment analysis: ROI modeling for major decisions (India build, Pigment, BI tooling, and other infrastructure replacements).
Strategy development and original insight
Peer benchmarking: quarterly comparison of KLD vs. PE-backed peers at $300M+ on close cycle, DSO, EBITDA margin, and headcount ratio.
Strategy memos: one-page financial impact write-ups for key decisions, written to go directly to the CFO and ELT as-is.
KPI framework: define scorecards by group (Collections, Analysts, FP&A, Sales Ops) with baseline, target, and measurement.
Identify patterns in the data the US team hasn't seen, and surface them unprompted.
ELT pre-reads: financial analysis, scenario tables, and recommendation summaries for executive meetings.
Qualifications
Financial Modeling:
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.
Expert Excel across dynamic models with scenario toggles, sensitivity tables, named ranges, and zero hardcoded assumptions.
Experience building PE-grade deliverables (EBITDA bridges, rolling forecasts, investor packages, scenario memos) in live contexts.
Pigment, Adaptive, Anaplan, or similar is non-negotiable; you will administer the platform from day one.
Technical Systems:
Python (pandas, requests, API calls) to build and maintain data pipelines without IT assistance.
SQL to query Oracle at GL level, validate data, and build reconciliation logic.
REST API experience reading and writing via API (Pigment API and Claude API).
LLM API familiarity with the ability to co-build AI agents, write system prompts, and validate outputs.
Strategy and insight:
Ability to translate complex financial analysis into a crisp one-page executive narrative.
Experience working directly with CFO- or PE-sponsor-level leadership on financial analysis.
Comfort operating in ambiguity: build the model when the inputs aren't clean and the question is still forming. PE-backed company experience or direct exposure to PE exit processes is a strong plus.
Leadership and communication:
Exceptional written English; strategy memos are read by CFO, ELT, and PE sponsors without editing.
Self-directed: identifies what needs building and builds it without a task list. Mentors the Financial Model Analyst and FP&A Data Engineer on modeling standards and output quality.
MBA from a top institution is preferred but not required if experience speaks for itself.
Driving Career Growth, Benefit Excellence: The KLD Advantage
At KLD we invest in employees and their families by placing their wellbeing first. We offer competitive total compensation that includes base pay, bonus potential, inclusive benefits, wellness programs, and perks. We use market and industry data to inform pay decisions while considering geography and labor markets, individual experience, and business needs. India compensation is based upon the local competitive market.
Paid time off, that offers various time off options to help employees maintain a work-life balance, such as Casual, Earned, Sick, Special Leave, and Holidays
Ongoing learning and development, a focus on continuous professional development through various training and education reimbursement programs
A diverse and inclusive workplace where we all learn, grow, and achieve the greatest heights…together
A surrounding team of mission-driven individuals who genuinely love what they do
Free, fun, interactive and incentivized global wellness program that promotes the wellbeing of our employees
India compensation is based upon the local competitive market
Who We Are
KLDiscovery provides technology-enabled services and software to help law firms, corporations, and government agencies solve complex data challenges. With offices in 26 locations across 17 countries, KLDiscovery is a global leader in delivering best-in-class data management, information governance, and eDiscovery solutions to support the litigation, regulatory compliance, and internal investigation needs of clients. Our Nebula Ecosystem provides powerful end-to-end eDiscovery and enterprise-grade information governance. Through its global Ontrack data recovery business, KLDiscovery delivers world-class data recovery, disaster recovery, email extraction and restoration, data destruction, and tape management.
We Provide Equal Employment Opportunity.
At KLDiscovery we believe that inclusion and diversity make us stronger. We are committed to fostering an inclusive environment for all employees that enhances wellbeing and belonging. We welcome and celebrate individuals of all backgrounds, experiences, and perspectives.
We do not discriminate on the basis of race, color, religion, gender, pregnancy, gender identity, sexual orientation, national origin, age, disability, genetic information, veteran status, or any other protected status. We are happy to support you with any accommodation request at any stage in our hiring process.
Originally posted on Himalayas