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DualEntry

AI-native ERP automating mid-size finance operations

Lead Analytics & Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeNew York, NY, USA

About the Job

Requirements

  • A bachelor's degree or above in Math, Economics, Bioinformatics, Statistics, Engineering, Computer Science, or another quantitative field, plus at least 5 years of industry experience as a Data Scientist.
  • Hands-on experience with a modern data stack such as Fivetran, Snowflake, dbt, Looker, Hex, or Hightouch, or equivalent tools.
  • Hands-on experience with data orchestration platforms such as Airflow, Dagster, or Prefect.
  • Hands-on experience with business intelligence tools, preferably Retool, Looker, Mode, Tableau, or equivalent, and experience distributing data insights through reports and dashboards.
  • Strong Python experience, including NumPy, pandas, and scikit-learn, across exploratory data analysis, predictive modeling, and applying machine learning techniques to marketing-specific problems.
  • Strong knowledge of SQL and efficient query writing, preferably using Snowflake, BigQuery, or Redshift.
  • A proven track record of shipping improvements with engineering, product, and go-to-market organizations.
  • A strong perspective on the data science engineering development cycle, including data modeling, version control, documentation, testing, and codebase development best practices.
  • Familiarity with business-to-business enterprise sales cycle metrics and processes.
  • Ability to work effectively in a fast-paced, continuously improving startup environment focused on solving problems with iterative technical solutions.
  • Experience at a high-growth startup.

Responsibilities

  • Stand up a Data & Analytics function from the ground up, working with leaders and teams to establish appropriate key performance indicators and insights across the organization.
  • Develop full-stack analytics engineering solutions, building models to consume, transform, and expose data internally and externally.
  • Work with different teams to capture, move, store, and transform raw data into actionable insights.
  • Collaborate with product, engineering, data, and design teams to develop prioritized product roadmaps and measure success.
  • Turn insights into action.
  • Set up data processes, tools, and systems that support scalable decision-making.
  • Drive experimental design, testing agendas, and best practices.

About the Company

DualEntry

AI-native ERP automating mid-size finance operations

DualEntry provides an AI-powered ERP platform for mid-sized businesses to manage finance and accounting. It runs as a cloud-based SaaS that automates reconciliations, reporting, compliance, and multi-entity accounting, with real-time dashboards and anomaly detection, and can migrate data in 24 hours without external consultants. It targets mid-sized firms that have outgrown lightweight tools by offering AI-driven automation and multi-entity support that replaces legacy software. Its goal is to help finance teams run operations more smoothly and quickly with an adaptable ERP upgrade path and real-time financial insights.

Company size
51-200
Company stage
Series A
Total funding
$96M
Headquarters
New York City, New York
Founded
2024

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