Chaitanya Vullaganti

Enterprise Cash Flow Forecasting & Financial Operations Platform

Designed and delivered an end-to-end cash flow forecasting and financial operations platform on Palantir Foundry for treasury and FP&A — governed Bronze/Silver/Gold pipelines, a semantic finance Ontology, ML-based monthly forecasting, and an OSDK-powered React console.

• Modeled a finance ontology spanning CashTransaction, GLEntry, CashFlowForecast, MonthlyCashFlowStatement, and ReconciliationBreak, with link types connecting transactions to accounts, forecasts, and exceptions.
• Built ingestion and curation pipelines in Pipeline Builder and Code Repositories for bank transactions, GL entries, chart of accounts, and reference data; tuned PySpark jobs to stabilize month-end workloads.
• Implemented data quality expectations, reconciliation logic, and governed Action Types for break assignment, forecast overrides, and approvals with object-level permissions for treasury roles.
• Delivered Workshop applications (CFO Cash Dashboard, Forecast vs Actuals, Line Item Explorer, Reconciliation Workbench) and a React/TypeScript OSDK application for workflows beyond standard Workshop.
• Designed a Bronze, Silver, and Gold data architecture on Foundry following lakehouse principles across ingestion, curation, ML, Ontology, and application layers.

Collections Management System — Real-Time, Event-Driven Platform on Foundry

Replaced a legacy Oracle BRM batch collections engine across a production portfolio of 921K billing accounts and 19.7M invoice records — reducing time-to-action from a nightly 24-hour batch cycle to minutes via event-driven eligibility.

• Architected CDC and batch merge pipelines across six Oracle BRM tables using LEFT ANTI JOIN merge with timestamp-based deduplication; built incremental PySpark transforms with derived ageing analytics.
• Designed an eight-object-type ontology with dual state machines (collection record: 5 states / 10 transitions; collection action: 7 states / 12 transitions) and cascading exit logic.
• Authored 15+ production TypeScript Ontology Functions and configured Automate monitors for real-time entry plus full lifecycle automation, removing routine manual handling on standard-path cases.
• Led parallel-run migration against legacy batch with rollback capability; delivered initial production sweep creating 1,917 collection records and 26,749 collection actions.

AML Alert Manager & Case Manager — Anti-Money Laundering Workflows

Developed and delivered end-to-end Foundry applications (Alert Manager, Case Manager) to support AML workflows for a banking client — translating business requirements into production features.

• Built and maintained ingestion pipelines and operational tooling to onboard historical and daily transactional data from legacy systems into Palantir Foundry.
• Designed Pipeline Builder transforms and loaded curated datasets into the Foundry Ontology to standardize entities and relationships for compliance use cases.
• Implemented business rules and validation logic enabling automated alert triage and case creation while preserving auditability and traceability.
• Developed Workshop apps for alert review, investigations, SAR preparation, and FINCEN filing; integrated SAR submit/rework into Case Manager.
• Led feature demos with business stakeholders and compliance SMEs; incorporated feedback through sprint planning, grooming, and story refinement.
• Collaborated with Data Ingestion, Downstream Processing, and Application Development to align data models and accelerate time-to-value.
• Monitored and troubleshot production pipelines; investigated data quality issues and coordinated remediation with engineering and operations.
• Applied Agile practices; documented designs, runbooks, and onboarding guides; mentored engineers on Foundry best practices, ontology design, and pipeline debugging.

Real-Time Streaming & Batch Operations — Ontology, Workshop & Databricks Pushdown

Developed and optimized real-time streaming and batch pipelines in Palantir Foundry, governed Ontology for devices/circuits/outages, Workshop applications, and a Databricks compute-pushdown proof of concept.

• Managed multiple development branches ensuring seamless ingestion, transformation, and streaming of clean, standardized data.
• Monitored pipeline health dashboards continuously — resolving warnings, errors, late data, and schema changes to prevent outages.
• Scaled compute and fine-tuned cluster configurations and partition keys for growing volumes, optimizing performance and cost.
• Managed Git versioning with pull requests and release schedules for stable, auditable production deployments.
• Enhanced correlation models with new sources and business rules — improving incident detection and reducing unnecessary field dispatches.
• Designed cleansing in Pipeline Builder (deduplication, imputation, unit translation, schema alignment).
• Built Workshop apps with overlays, widgets, and RBAC for interactive exploration and secure ticketing.
• Created Ontology Object/Action/Link Types for devices, circuits, and outages with property constraints, lineage, and RBAC.
• Delivered Quiver/Contour dashboards for pipeline health, data quality, outage maps, and operational KPIs.
• Developed PySpark transforms and reusable TypeScript/Spark SQL UDFs in Code Repositories and Workbooks.
• Built Databricks Delta/Iceberg compute-pushdown POC; benchmarked Photon, serverless, and Pipeline Builder for compute strategy.

Enterprise CRM on Foundry — Ontology, Pipeline Builder, Workshop, Automate & AIP

Built a comprehensive CRM using Code Workspaces, Ontology Manager, Workshop, Pipeline Builder, Automate, and Vertex — with AIP/LLM synthetic data and TypeScript auto-assignment by state and industry.

• Built automated Pipeline Builder ETL; performed analysis and cleansing on company/people datasets in Python and SQL Workbooks.
• Created Ontology Object Sets and Action Types; implemented AIP Logic / LLM synthetic data and specialized table splits.
• Developed TypeScript Automate functions for auto-assigning employees to new clients based on state and industry.
• Designed Workshop UI with visualizations, filters, custom widgets, overlays, variables, functions, and real-time metrics.

Healthcare Data Intelligence & Predictive Analytics Platform

Built predictive analytics and machine learning solutions supporting healthcare operations, risk assessment, and business intelligence.

• Built predictive models for risk assessment, population segmentation, and operational forecasting across structured and unstructured datasets.
• Delivered end-to-end modeling workflows as modular R scripts; applied supervised/unsupervised techniques selected against precision, recall, ROC-AUC, and cross-validation.
• Built NLP workflows for free-text feedback analysis; developed Tableau dashboards for leadership KPIs.

Enterprise Business Intelligence & Reporting Platform

Built enterprise BI and reporting solutions on large-scale transactional data — SQL analytical datasets, interactive Tableau dashboards, and KPI reporting.

• Designed analytical data models and complex SQL (CTEs, window functions, ranking, aggregations) into executive-ready datasets.
• Built interactive Tableau dashboards with calculated fields, parameters, drill-downs, and dynamic filters; automated recurring reporting.