About The Position

Dave is a financial app on a mission to build products that level the financial playing field. As our first Senior AI Reconciliation Analyst, you'll establish the reconciliation foundation for Dave's data systems — designing the pipelines, anomaly rules, and AI-powered matching logic that keep our financial data trustworthy and audit-ready. You'll sit at the intersection of data engineering, finance, and operations, serving as the technical lead who helps Engineering, Finance/Accounting, and Reconciliation Operations move faster and catch problems before they become incidents. This role is for someone who thinks in systems, is energized by financial data complexity, and wants to build something foundational from the ground up.

Requirements

  • 5+ years of experience in data analytics, data engineering, or financial data roles — ideally with direct exposure to reconciliation, settlements, or financial operations.
  • Deep SQL proficiency and strong Python skills (pandas, PySpark, or equivalent); experience with DBT a plus.
  • Hands-on experience with Snowflake and/or Databricks, including pipeline development, scheduling, and data modeling.
  • Familiarity with ACH transaction cycles, payment rails, or financial settlement processes — you understand why timing differences exist and how to model around them.
  • Experience building anomaly detection logic, whether rule-based, statistical, or ML-driven.
  • Exposure to probabilistic/fuzzy matching techniques for entity resolution or transaction matching.
  • Strong cross-functional communication skills — you can translate a data quality issue into clear language for a Finance partner and a technical spec for an Engineer.
  • Practical AI/ML knowledge, including supervised and unsupervised methods relevant to reconciliation — anomaly detection (isolation forest, autoencoders), clustering for transaction grouping, and classification models for match/no-match decisions.
  • Experience working with LLMs or AI-assisted tooling (e.g., prompt engineering, LLM-based data extraction, or AI-augmented workflow automation) to accelerate analysis and reduce manual review.
  • Experience in fintech or financial services strongly preferred.
  • Bachelor's degree in a field requiring analytical or structured thinking (e.g., STEM, Economics, Finance); Master's degree preferred.

Nice To Haves

  • Experience with dbt
  • Master's degree

Responsibilities

  • Build the reconciliation foundation. Design and implement the data infrastructure that reconciles transactions across internal systems (e.g., operation, ledger) and external partners (ACH networks, banking rails, payment processors), ensuring every dollar in equals every dollar out.
  • Lead anomaly detection and rules development. Develop and maintain a library of anomaly detection rules — covering timing differences, partial matches, unexpected delays, and true errors — and evolve them over time using ML-based signals as data matures.
  • Implement AI-powered matching. Apply probabilistic and fuzzy matching techniques to automatically resolve ambiguous or near-match transactions, reducing manual review queues and improving straight-through processing rates.
  • Flag and triage unmatched records. Build real-time and batch pipelines that surface unmatched, delayed, or anomalous transactions to the right stakeholders, with enough context for fast resolution.
  • Partner cross-functionally as the technical lead. Serve as the primary data partner for Engineering (system integration and pipeline reliability), Finance/Accounting (period-end close, audit support), and Recon Operations (workflow tooling, exception handling).
  • Define data quality standards. Establish validation frameworks that distinguish expected timing lags from genuine discrepancies, and document data contracts between upstream systems.
  • Drive automation and process improvement. Identify and eliminate manual reconciliation workloads through scalable pipelines, alerting systems, and self-serve tooling for operations teams.
  • Elevate the team. Share reconciliation and data quality best practices, mentor analysts, and help establish this function as a core capability within the Analytics org.

Benefits

  • Opportunity to tackle tough challenges, learn and grow from fellow top talent, and help millions of people reach their personal financial goals
  • Flexible hours and virtual-first work culture with a home office stipend
  • Premium Medical, Dental, and Vision Insurance plans
  • Generous paid parental and caregiver leave
  • 401(k) savings plan with matching contributions
  • Financial advisor and financial wellness support
  • Flexible PTO and generous company holidays, including Juneteenth and Winter Break
  • All-company in-person events once or twice a year and virtual events throughout to connect with your team members and leadership team
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