More than 15 years across enterprise SaaS, banking, and financial services, building the planning systems, portfolio governance, and executive cadence leaders decide with. 100% adoption of a new Jira operating model in four months at HashiCorp. $1.6M in incremental 2023 revenue from cloud monetization at Dayforce. A Wells Fargo vendor-model framework that cut deployment SLAs from 18 months to 4.
That means scored intake and business cases before funding, capacity forecasts behind roadmaps, executive reporting on a regular cadence, and validation of AI productivity claims before investment decisions. The work covers what to prioritize, what to fund, what to pause, and how to measure the result.
Four results from the record, each shown against its starting point. Switch between the two states, or open a row for context.
As a founding member of the AI Model Development Center of Excellence, I authored the SR 11-7-aligned Vendor Model Development Lifecycle and trained US and India CoE data scientists on it. Deployment for vendor models dropped from an 18-month SLA to 4. The framework is still in use and influenced how internal models are developed.
Program-managed loan origination automation across underwriting and decisioning. For the 70-80% of applications the rules engine decided, decision time went from 24-48 hours to seconds. The remainder were routed to mandatory human review.
Ran R&D executive KPI and portfolio reporting for the VP of R&D. Leadership went from reading numbers two weeks old to reading numbers two days old.
Built a forecasting model that reached ~90% adoption across four R&D product groups and was later used for OKR planning. A pilot team cut its estimate variance in half, from 40% to 20%, against a ~10% model target.
My career started in commercial roles in energy trading and liquid logistics in India, then ran through an MBA at Syracuse and into regulated financial services. At Wells Fargo that meant AML product releases, then a $200M+ BCBS 239 data governance program, then a founding seat on the AI Model Development Center of Excellence. That work combined data governance, regulatory delivery, and model risk management.
At Dodge & Cox, as operating partner to the CTO, I directed prioritization of a $15M technology portfolio run by roughly 200 matrixed staff, and led the target-state architecture and migration blueprint to consolidate four fragmented data groups onto a unified Snowflake/Azure platform, building a 137-epic migration backlog with Publicis Sapient.
At Dayforce, I led an EPMO of 4 direct reports covering 19 cross-functional programs, and led cloud monetization that generated $1.6M in incremental 2023 revenue and ~$4.1M in annualized recurring impact. At HashiCorp, an IBM company, I moved R&D teams onto a new Jira operating model at 100% adoption in four months.
Through SR Advisory, I build executive decision systems and advise a Series B SaaS company on AI-enabled Customer Success pilots. Separately, I provide GTM advisory to a GreenTech venture in which I hold equity. MBA in Finance & Marketing from Syracuse. PMP certified.
A defined-scope contract to build a planning and reporting system for R&D leadership. The new Jira operating model reached 100% adoption in four months. Separately, I led an 80+ team change program that was adopted as the R&D standard and ran about 30% faster than plan in key tracks. The forecasting model reached ~90% adoption across four product groups and was later used for OKR planning.
Led cloud monetization and optimization across environment pricing, rationalization, and order-to-cash execution. The program generated $1.6M in incremental 2023 revenue and ~$4.1M in annualized recurring impact while decommissioning ~800 uncontracted environments. Alongside it, I co-led the ADAM HCM post-merger integration, which unblocked $600K in remediation.
Founding member of the AI Model Development Center of Excellence, covering structured and unstructured AI/ML use cases. Authored the SR 11-7-aligned Vendor Model Development Lifecycle, which cut the vendor-model deployment SLA from 18 months to 4, and trained US and India CoE data scientists on it. The framework is still in use. In parallel, led the Analytics Target Operating Model supporting 10,000+ analysts, backed by a ~$30M modeled three-year ROI case.
Built across Dodge & Cox, Dayforce, HashiCorp, and advisory work. Each practice builds on the one before it.
At Dodge & Cox, intake scoring and cross-program decision frameworks set priorities across a $15M technology portfolio. At Dayforce, intake and FP&A-backed business cases decided how 19 programs were prioritized and funded. This makes trade-offs visible before funding is committed.
At Dayforce, the planning model linked the Long-Range Plan to annual execution through quarterly reforecasts, with spend and FTE allocation tracked against the funded plan alongside FP&A. At HashiCorp, capacity forecasting gave R&D leaders a measured delivery forecast to plan against.
Dayforce SLT and operating-committee QBR scorecards went out within 15 days of each earnings call. HashiCorp R&D executive reporting went from a 14-day lag to 2 days. A consistent cadence keeps decisions tied to current data.
At HashiCorp, I validated AI productivity claims before a six-figure standardization decision. The same discipline supported the modeled ROI case for the Wells Fargo Analytics Target Operating Model. Value tracking links results back to the original business case.
Open to Director and Senior Director roles, with selective VP opportunities, in strategy & operations, enterprise transformation, and portfolio governance across enterprise SaaS and financial services. Based in Scottsdale, AZ.