Mission-Focused Data Scientist & Visualization

TLN Worldwide Enterprises Inc; Washington (District of Columbia); Presencial; USD 110.000 - 160.000; Jornada completa

Descripción de la vacante

TLN Worldwide Enterprises Inc is seeking a Data Scientist to support the PRM Office with data analysis, visualization, and reporting across programmatic, financial, and humanitarian data. The role emphasizes dashboarding, data management, and stakeholder communication to inform policy decisions.

The ideal candidate has hands-on Python, R, and SQL experience, proficiency in Power BI or Tableau, and a strong ability to translate complex questions into data-driven outputs for diverse audiences.

Formación

• Bachelor’s degree in a relevant field.
• 3–5 years of data science or analytical experience.
• Strong analytical and quantitative skills.
• Experience with Python, R, and SQL.
• Experience with Power BI or Tableau.
• Ability to communicate complex concepts to non-technical audiences.

Responsabilidades

• Perform data analyses and visualizations to identify insights across programmatic datasets.
• Develop and maintain dashboards, reports, and visualizations.
• Collaborate with stakeholders to translate questions into analyses.
• Ensure data quality, documentation, and governance for data products.
• Communicate findings to policymakers and technical teams in clear terms.
• Support data management, security, and privacy practices.

Conocimientos

Python

R

SQL

Data analysis

Analytical thinking

Educación

Bachelor's degree

Herramientas

Power BI

Tableau

Descripción del empleo

TLN Worldwide Enterprises Inc is seeking a Data Scientist to support the PRM Office with data analysis, visualization, and reporting across programmatic, financial, and humanitarian data. The role emphasizes dashboarding, data management, and stakeholder communication to inform policy decisions.

The ideal candidate has hands-on Python, R, and SQL experience, proficiency in Power BI or Tableau, and a strong ability to translate complex questions into data-driven outputs for diverse audiences.