Data Scientist (Temp) — Remote/Hybrid, Predictive Analytics

Garden Life Dev

Goldsboro (NC)

Ibrido

USD 59.000 - 96.000

Tempo pieno

14 giorni+

Una candidatura completa in un minuto

Curriculum e lettera di presentazione personalizzati, pronti da inviare.

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Vantaggi offerti da questo lavoro

Health benefits
Orientation before assignment
Support throughout assignment

Descrizione del lavoro

Garden Life Development seeks a Data Scientist for a full-time temporary (W-2) role in North Carolina. You will analyze large datasets, design predictive models, and present findings to guide business decisions.

The position supports on-site, hybrid, or remote work depending on the project, with competitive hourly pay. Responsibilities include building dashboards, maintaining data pipelines, and translating business questions into analytic approaches.

Competenze

  • Experience with data science or advanced analytics.
  • Strong Python or R, SQL skills and ML libraries.
  • Solid statistics foundation.
  • Bachelor's degree in a related field or equivalent experience.

Mansioni

  • Analyze large datasets to find patterns, trends, and insights.
  • Design and build predictive models and ML algorithms.
  • Collect, clean, and prepare structured and unstructured data.
  • Build efficient data workflows.
  • Translate business questions into analytic approaches.
  • Present findings with clear visualizations.
  • Evaluate and improve models over time.
  • Build dashboards to track key metrics.

Conoscenze

Python or R
SQL
ML libraries
Statistics

Formazione

Bachelor's degree in related field

Descrizione del lavoro

Garden Life Development seeks a Data Scientist for a full-time temporary (W-2) role in North Carolina. You will analyze large datasets, design predictive models, and present findings to guide business decisions.

The position supports on-site, hybrid, or remote work depending on the project, with competitive hourly pay. Responsibilities include building dashboards, maintaining data pipelines, and translating business questions into analytic approaches.

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