Senior Data Scientist Accounting
@ Mercury

Hybrid
$180,000
Hybrid
Full Time
Posted 22 days ago

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XXXXXXXX XXXXXXXXX XXXXXX***** @mercury.com
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Job Details

Overview

At Mercury, as a Senior Data Scientist Accounting, you will work on the development of analytics tools and data-driven solutions for Financial & Accounting Workflows. You will partner with product, engineering, and financial teams to build self-serve dashboards, data pipelines, and machine learning solutions to enhance core accounting systems and broader financial processes.

Responsibilities

  • Partner with Financial & Accounting Workflow stakeholders to establish success metrics.
  • Collaborate with product and engineering teams to design experiments and analyze outcomes.
  • Drive the launch and iteration of new products informed by data insights.
  • Prototype and implement ML/AI solutions for tasks like autocategorization and reconciliation.
  • Build dashboards, data pipelines, and reports for self-serve analytics.

Requirements

  • 3–5 years experience in product analytics or data science, especially in financial workflows.
  • Fluency in SQL and proficiency in Python or similar statistical programming languages.
  • Experience with designing and analyzing A/B tests and applying causal inference methods.
  • Hands-on experience with modern data stack tools such as Snowflake, dbt, and reporting platforms.
  • Background with ERP/accounting systems like QuickBooks, Xero, or NetSuite.
  • Experience with applying ML or GenAI to product challenges.
  • Strong organizational and communication skills to manage multiple priorities.

Compensation & Benefits

The total rewards package includes a competitive base salary, equity (stock options), and benefits. Salary offers are based on experience, geography, and internal pay equity.

Key Skills/Competency

  • Data Science
  • Accounting
  • SQL
  • Python
  • ML/AI
  • Data Pipelines
  • Dashboards
  • A/B Testing
  • ERP Systems
  • Financial Analytics
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How to Get Hired at Mercury

🎯 Tips for Getting Hired

  • Customize your resume: Tailor your experience to financial analytics.
  • Research Mercury: Understand their fintech and accounting focus.
  • Prepare technical insights: Showcase SQL, Python, and ML expertise.
  • Practice case studies: Demonstrate data-driven problem solving.

📝 Interview Preparation Advice

Technical Preparation

Review SQL queries and data manipulation.
Practice Python coding challenges.
Study statistical testing and A/B experiments.
Familiarize with modern data stack tools.

Behavioral Questions

Describe a challenging data project.
Explain effective cross-functional communication.
Discuss prioritizing multiple projects.
Share experience in stakeholder collaboration.

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