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// DIRECTOR OF FINANCE · PE-BACKED HEALTHCARE

The finance system behind M&A, FP&A, payor strategy, and post-close execution.

Director of Finance at a PE-backed healthcare platform. I own the model, present it to the sponsor, and run the cadence that holds the value-creation plan together. Built for sponsors who want a finance leader who can do both.

NOWDirector of Finance
BASEDTexas
BUILDINGAI-assisted finance reporting workflows
DEAL
OPERATOR
SINCE 2019
Strengthen Your Business SavvyApr 2026✓ Business & Financial ModelingMay 2026Spec. Mergers & AcquisitionsJan 2026Spec. AI Engineer for DevelopersMay 2026✓ Fundamentals of Quant ModelingSep 2017✓ Professional Data ScientistNov 2022✓ Global Financial MarketsSep 2017✓ Strengthen Your Business SavvyApr 2026✓ Business & Financial ModelingMay 2026Spec. Mergers & AcquisitionsJan 2026Spec. AI Engineer for DevelopersMay 2026✓ Fundamentals of Quant ModelingSep 2017✓ Professional Data ScientistNov 2022✓ Global Financial MarketsSep 2017✓
$100M+
M&A DEAL VALUE OWNEDCumulative diligence · PE-backed healthcare · 2021–2026
130+
PHYSICIANS · 100+ LOCATIONSMulti-state platform · 11 states · Beacon · 2021–2023
20%
TOP-LINE LIFTPayor renegotiation · owned end-to-end · FY contribution
2,600+
CENTERS, NATIONAL SCALEPayor-mix & revenue analytics · Fresenius · 2021

Finance leadership scope.

// CURRENT SEAT · NEW PROMISE NEUROPATHY
Revenue scope
$20M+ revenue
Multi-state specialty healthcare platform. PE-backed. Top-line in growth mode.
M&A volume owned
$100M+ cumulative
Diligence and underwriting across the current and prior PE-backed platforms.
Reports to
CEO · PE sponsor
Direct line into the operating partner and the executive team.
Functions owned
M&A · FP&A · Payor · Close-support
Acquisition diligence, FP&A, payor strategy, and the analytics behind monthly close and board reporting.
Systems owned
NextGen · Azure SQL · Excel/Python
Revenue-cycle data (charges, payments, AR) consolidated into the FP&A reporting layer I run.
Operating footprint
Multi-state, multi-clinic
Clinical operations across multiple states with payor-mix variance and rate-sensitivity exposure.
// THE THROUGH-LINE

Each case below is real work I owned and presented to a sponsor or board. The workbooks shown here are reconstructed with sanitized assumptions for confidentiality. Pull one, then book a call and we'll go through the assumptions, the sensitivities, and what I'd own differently today.

Operating cadence.

// 01b — HOW I RUN THE FINANCE FUNCTION

The case studies show outcomes. This is the rhythm underneath them — the cadence that turns deal models, payor strategy, and FP&A into a finance function a sponsor can actually run a business on.

Daily
Production & cash flash
Cash position, prior-day production by clinic, AR aging deltas. The thirty-second read on whether anything broke overnight.
Weekly
KPI scorecard
Revenue, collections, denials, productivity by clinic and provider. Variance against forecast with named owners.
Monthly
Close + board pack
Close support, EBITDA bridge against budget, KPI dashboard, value-creation tracker. The package the sponsor sees.
Quarterly
Reforecast + sponsor update
Re-baseline the year, refresh the value-creation plan, surface the calls leadership needs to make in the next 90 days.
Annual
Budget + 3-year plan
Bottoms-up budget, top-down sponsor expectations, M&A pipeline assumptions, capital plan. The instrument everything else is measured against.

Operating metrics I watch.

// 01b — HEALTHCARE FINANCE KPI VOCABULARY

The six numbers a healthcare finance leader has to read fluently. Anyone in this seat should be able to define them, defend them, and know what action each one drives. This is the vocabulary every operating conversation I'm in actually uses.

// 01
Net Collection Rate (NCR)
Collected dollars divided by expected collectible dollars (allowed). The north-star measure of revenue cycle health.
What I watch forSustained NCR below 90% in a multi-payor mix — signals contract leakage or RCM friction.
// 02
Days in AR
Accounts receivable balance over average daily charges. The cash-cycle indicator that drives working capital.
What I watch forDrift above 45 days, or AR>120 climbing — tightens covenant headroom fast.
// 03
Denial rate
Percentage of claims initially denied by the payor. The earliest signal of RCM and front-end friction.
What I watch forAny denial reason concentration — a payor / CPT / location pair that explains most of the volume.
// 04
Payor mix
Share of revenue by payor class (commercial / Medicare / Medicaid / self-pay). Drives every rate-sensitivity analysis.
What I watch forConcentration in any single commercial payor > ~25% — renegotiation risk and contract dependency.
// 05
Charge lag
Days between date of service and charge entry. The clean leading indicator of revenue cycle backlog.
What I watch forLag > 5 days at any clinic — suggests provider documentation gaps before AR even starts ticking.
// 06
Provider productivity (wRVU)
Work-RVUs per provider per period. The capacity-utilization measure that anchors compensation and staffing decisions.
What I watch forVariance against benchmarks by sub-specialty — not raw wRVU. Comparable provider in comparable market.

The body of work.

// 01 — FIVE CASE STUDIES · FIVE MODELS
[01] VALUE CREATION · PAYOR STRATEGY

How I owned the payor renegotiation that drove a 20% top-line lift.

The problem
Multi-clinic platform with manual reporting that obscured payor-level economics. Renegotiation conversations were anecdotal, not analytical.
What I owned
Built the payor-mix and rate-sensitivity analysis end-to-end. Modeled contribution by site, by payor, by procedure. Presented the renegotiation case to leadership and anchored the strategy on the contracts that mattered.
The outcome
Renegotiation contributed to a 20% top-line revenue lift. Reporting cycle time cut ~40% along the way.
Numbers and exhibits sanitized for confidentiality. Methodology and structure are real.
Read more about it
[02] HEALTHCARE M&A · TUCK-IN

How I led diligence and stood up Day-1 reporting the morning a tuck-in closed.

The problem
Multi-site specialty platform pursuing tuck-ins. Diligence had to move fast and clean. Covenant tracking, ASC 805 fair-value, and integration risk were all gating close.
What I owned
The full deal underwriting end-to-end: Sources & Uses, purchase price waterfall, FVA step-ups, accretion/dilution, synergy build. Managed the QoE with Transaction Advisory and led the integration finance plan.
The outcome
Day-1 reporting, controls, and covenant tracking live the morning of close. Sponsor walked into the first board meeting with the numbers already running.
Numbers and exhibits sanitized for confidentiality. Methodology and structure are real.
Read more about it
[03] M&A · MULTI-STATE ROLLUP

How I standardized diligence across a 100-location PE rollup and cut close time 20%.

The problem
PE-backed multi-state specialty platform. Acquisition pace required standardized diligence and a defensible returns model on every target.
What I owned
The LBO and diligence framework applied to every target: capital structure, debt paydown, IRR/MOIC sensitivity, integration assumptions. Built the performance dashboards in Python and SQL that the operating team ran on.
The outcome
Transaction closing time reduced 20%. Network scaled to 130+ physicians, 100+ locations, 11 states on the same playbook.
Numbers and exhibits sanitized for confidentiality. Methodology and structure are real.
Read more about it
[04] FORTUNE 500 · OPERATING SYSTEMS

What I learned about systems and leadership from inside the Fortune 500.

The situation
Two Fortune 500 environments early in my career. A Fortune 50 telecom serving 145M+ wireless customers. A national dialysis network of 2,600+ centers and 190,000+ patients. Scale changes how you build reporting, run decisions, and structure span of control.
What I picked up
Operating-system thinking. Reporting cadences that hold up across thousands of operating units. Standardized analytics so a regional VP sees the same number the CFO sees. A healthy respect for which decisions get owned at the edge and which get owned at the center.
What carried over
The same systems mindset now applied to every PE-backed platform I work on. Standardize the spine; localize at the edges. Run reporting that breaks predictably, not silently.
Read more about it
[05] FINANCE AUTOMATION · CRE UNDERWRITING

How I own a CRE underwriting automation product end-to-end, on the side.

The problem
CRE sponsors spend hours per deal extracting rent rolls, building models, and assembling sponsor-grade reporting. Most underwriting is still manual.
What I own
The full product. AI rent-roll extraction, NOI / cap rate / IRR engine, sponsor-grade reporting layer. I architected the finance logic; the stack (OpenAI, Next.js, Postgres) is the delivery mechanism.
The outcome
Live at DealManagerAI.com. Real CRE sponsor running real deals through it. Treated as evidence I can scope and ship finance automation, not as the headline of what I do.
Read more about it

Sample board artifacts.

// 01c — SANITIZED · REPRESENTATIVE

Two artifacts I run every month. The EBITDA bridge is what the sponsor opens first. The value creation tracker is what we work against between board meetings. Numbers and initiative names are illustrative; structure and methodology are real.

EBITDA Bridge · LY → LTMFY representative
LY EBITDA
$5.0M
+ Volume
+0.8M
+ Payor mix / rate
+1.1M
+ M&A synergies
+0.4M
− Opex inflation
−0.3M
− Integration
−0.2M
LTM EBITDA
$6.8M
Reads in 15 seconds. The sponsor wants to know what changed and who owns each lever — the bridge is the answer in one panel.
Value Creation TrackerLive, refreshed monthly
InitiativeBaselineTargetImpactOwnerStatus
Payor renegotiationNCR 88%NCR 91%+$1.1MDoFRealized
AR cleanup52 days38 days+$0.4M cashRCM · DoFIn flight
Tuck-in — State X—$0.4M syn.+$0.4MDoF · COOOn plan
Provider productivity4.5 wRVU/d5.2 wRVU/d+$0.3MCOO · DoFRealized
FP&A automationManualDaily auto+0.1 FTEDoFRealized
Denial reduction9.2%6.0%+$0.2MRCMAt risk
Every initiative has a baseline, a target, an EBITDA / cash impact, and a named owner. No initiative gets a status without evidence.

The arc.

// 02 — CAREER + EDUCATION
2023 — NOW
New Promise Neuropathy
Director of Finance · Dallas
A PE-backed specialty healthcare platform delivering neuropathy care across multiple clinics in the Sun Belt. Director of Finance leading FP&A, acquisition diligence, and payor strategy across the platform.
2021 — 2023
Beacon Oral Specialists
Senior Financial Analyst · Dallas
A PE-backed (Blue Sea Capital) multi-state oral surgery platform that grew to 130+ surgeons across 100+ locations and 11 states. Finance lead on acquisition diligence and post-close integration. Standardized M&A frameworks cut transaction close time 20%.
2021
Fresenius Medical Care
Financial Analyst II · Dallas
The largest provider of dialysis care in North America. A 2,600+ center, 190,000+ patient network spanning Medicare, Medicare Advantage, and commercial reimbursement. Revenue forecasting and payor-mix analysis at national scale.
2019 — 2020
Verizon
Financial Analyst · Tulsa
A Fortune 50 telecom serving over 145M customers across wireless, broadband, and enterprise lines. Enterprise FP&A across global revenue streams. Financial reporting, scenario analysis, and modeling on large-scale data lakes.
EDU · 2021University of OklahomaMaster of Science in FinanceRestructuring & Leveraged Finance
EDU · 2018University of FloridaBachelor of Science in Business AdministrationBusiness Management

Credentials.

// 03 — SEVEN VERIFIED CREDENTIALS
DataCamp
DataCamp
AI Engineer for Developers

Verified by a 4-hour proctored build exam. Shipped an embedding-based retrieval chatbot with OpenAI structured outputs and conversation history.

May 2026Learn more →
Wharton
Wharton Online · UPenn
Business & Financial Modeling

The full Excel modeling discipline. Built a Markowitz portfolio that beat single-stock AAPL on real 2016 data, with the workbook and the deck to defend it.

May 2026 · SpecializationLearn more →
I
UIUC Gies College of Business
Mergers & Acquisitions

Six-course program: valuation, deal structuring, tax mechanics, accretion/dilution, IPO process. The vocabulary every M&A diligence conversation runs on.

Jan 2026 · SpecializationLearn more →
HBR
Harvard Business Review
Strengthen Your Business Savvy

Frameworks for leading with technology and AI, and making the strategic call when the right answer isn't obvious.

Apr 2026Learn more →
Wharton
Wharton Online · UPenn
Quant Modeling

The base layer of quantitative thinking. When deterministic, probabilistic, and optimization are the right tool, and when each is the wrong one.

Sep 2017Learn more →
DataCamp
DataCamp
Data Scientist

Production-grade data science foundation: Python, statistics, ML pipelines, and the discipline to ship a reproducible analysis.

Nov 2022Learn more →
Rice
Rice University
Financial Markets

Asset-class fluency: equities, fixed income, derivatives, currencies. The working vocabulary every valuation conversation runs on.

Sep 2017Learn more →

Finance automation I own.

// 04 — PRODUCTS AND WORKBOOKS I'VE SCOPED, BUILT, AND SHIPPED

A small set of finance products and reference workbooks I've owned end-to-end. Treat this as evidence that I can scope and ship the analytical infrastructure a finance org runs on — not as a software portfolio.

Where I fit.

// 05 — HONEST POSITIONING

The seat I'm built for

  • PE-backed lower- to mid-market healthcare. $20M–$150M revenue. Multi-site, multi-state, payor-exposed.
  • Director of Finance → VP Finance → CFO track. Hands-on enough to own the model. Senior enough to present it to the sponsor.
  • Operating cadence + M&A engine. Standing FP&A rhythm and 2–6 tuck-ins a year.
  • Sponsors who want a finance leader who runs the cadence and owns the analysis. Not one or the other.

What I'm not

  • Not a fund-side investment analyst. I run portfolio finance, not sponsor diligence.
  • Not a Big-4 controller. I lean on accounting partners for technical close work; I own the analytics and decision support around it.
  • Not a public-company controller. SOX, 10-Q rhythm, and Street-facing reporting are not where I've operated.
  • Not a generalist consultant. I work inside one platform, accountable for the same numbers month after month.

Open the model.
Then let's talk.

Twenty minutes. I'll walk through the assumptions, the sensitivities, and the parts I'd own differently if I were doing it today.

// WALKTHROUGH · 20 MIN
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Pick a time — I'll walk you through the model.

Twenty minutes. Open the workbook with me. Ask the hard questions about the assumptions.

{{ CALENDLY EMBED — calendly.com/sheharyarm/20min }}
// SEND ME THE MODEL
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I'll send it straight to your inbox.

// BOOK A CALL
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Let's talk.

Twenty minutes. Drop your info and I'll reach out to confirm a time.

// CREDENTIAL
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