Data Analyst, Supply — Drive Fill Rate & Operational Insights

Shiftsmart, Inc.; New York (NY); Hybrid; USD 90,000 - 130,000; Full time

Job summary

Shiftsmart, Inc. is seeking a Data Analyst to join our Supply team in New York City, with typically 3+ days per week in the office. You will build data models, run analyses, and drive actionable insights to optimize partner supply and fill rates across the marketplace.

Ideal candidates have 2–4+ years in analytics, strong SQL skills, and experience with Python for data analysis and modeling. You will collaborate cross-functionally to translate business needs into data-driven solutions.

Qualifications

• 2–4+ years of analytics, data science, data engineering, or similar analytical role.
• Strong SQL skills with ability to write complex queries.
• Experience with Python (pandas) for analysis and modeling.

Responsibilities

• Scale the Supply Model by expanding core DBT data tables to support decisions across the partner organization.
• Investigate and diagnose data anomalies and unexpected changes in business performance end-to-end.
• Operational Analytics: build and maintain BigQuery analyses and core data tables for day-to-day decisions.
• Maintenance and Reliability: maintain core data tables in DBT across the Supply team and related areas.
• Predictive Analytics: develop and iterate on predictive models to identify operational risks.
• Cross-Functional Collaboration: work with Supply, Marketplace, Partner Success, Product and Engineering to translate problems into data requirements.

Skills

SQL

Python

Analytical thinking

Tools

DBT

BigQuery

Job description

Shiftsmart, Inc. is seeking a Data Analyst to join our Supply team in New York City, with typically 3+ days per week in the office. You will build data models, run analyses, and drive actionable insights to optimize partner supply and fill rates across the marketplace.

Ideal candidates have 2–4+ years in analytics, strong SQL skills, and experience with Python for data analysis and modeling. You will collaborate cross-functionally to translate business needs into data-driven solutions.