金融数据求职

Created financial dashboards integrating sales, gross margin, promotion spend, and stockouts for 2,000+ store locations.

Conducted margin bridge analysis to decompose impact of pricing, mix shift, markdowns, and supply chain costs.

Extracted transaction-level sales data and structured SKU hierarchies using SQL and Alteryx for scalable ETL.

Identified $18.2M in gross margin leakage from poor markdown control and regional pricing misalignment.

Recommended regional promotions and SKU rationalization that boosted gross margin by 2.7%.

Collaborated with Inventory Planning to improve forecast accuracy of high-margin products.

Built full-cost client profitability models for 6 service lines, incorporating labor, travel, and overhead allocation methodologies.

Created dynamic PowerBI dashboard with filters by project, partner, service type, and geography, enabling on-demand reporting.

Identified that 14% of active clients were contributing negative profit margins, prompting pricing and scoping adjustments.

Enabled BD and senior partners to rank clients by long-term ROI and lifetime value rather than top-line revenue.

Incorporated the achieved results into FY planning and resource allocation for partner-level decision making.

Screened and modeled 25+ potential acquisition targets in the fintech space for a thematic growth platform.

Conducted detailed revenue and EBITDA bridge analysis and synergies modeling under multiple acquisition structures.

Performed Monte Carlo simulations in Python to calculate IRR and downside risk with volatility-adjusted forecasts.

Built DCF models with granular operating assumptions and scenario toggles for upside/downside analysis.

Benchmarked private company valuation against public and precedent transactions using CapIQ.

Synthesized the findings into 10-page IC memos that shaped pipeline prioritization and deal terms.

Managed quarterly OPEX planning and reporting process for a $2.2B global business unit, spanning R&D and Marketing.

Built and maintained budget tracking templates in Anaplan; linked to Tableau dashboards for cost center drill-downs.

Utilized Python to flag anomalies in historical spending trends and enforce updated accrual policies.

Partnered with FP&A and controllership to reconcile forecast vs. actuals during close cycles.

Highlighted areas of chronic underspend and enabled $4.5M reallocation to higher-return programs.

Reduced planning cycle by 60% through automation of repetitive inputs and workflows.

Built predictive CLV model using customer transactions, credit performance, engagement behavior, and acquisition cost.

Utilized XGBoost with feature importance to identify key drivers of long-term customer value.

Validated model accuracy through holdout testing and adjusted thresholds based on ROI sensitivity.

Integrated CLV outputs into Tableau to enable Marketing and Finance to track value creation across campaigns.

Led to a retargeting strategy based on the findings that improved retention among top 20% of customers by 11%.

Collaborated with CRM and analytics teams to integrate scoring into campaign automation systems.