Data Specialist

4 days ago


Princeton, United States Jobility Talent Solutions Full time

Title: Data Specialist

Location: Princeton NJ (Hybrid 1x day onsite per week)

Duration: 7 months contract

  • Data Collection and Analysis: Gather, clean, and analyze large datasets from various sources to support business insights and decision-making processes.
  • Data Quality Assurance: Ensure data accuracy and integrity by identifying and correcting data inconsistencies, performing regular audits, and maintaining updated databases.
  • Reporting and Visualization: Create reports, dashboards, and visualizations using tools like Tableau, Power BI, or Excel to communicate data findings effectively to stakeholders.
  • Database Management: Manage and maintain databases, including data storage, retrieval, and updating processes, to ensure data availability and efficiency across the organization.
  • Collaboration and Support: Work closely with data scientists, analysts, and business teams to support data-driven initiatives, troubleshoot data issues, and provide technical assistance as needed.


Quals--

**This position is hybrid- at least one day a week in the Princeton office**


  • Bachelor’s degree in Data Science, Computer Science, Statistics, or a related field; certifications in data analytics or database management are a plus.
  • Technical Skills: Proficiency in data management tools (e.g., SQL, Excel) and familiarity with programming languages such as Python or R for data processing and analysis.
  • Analytical Skills: Strong analytical and problem-solving skills with attention to detail to ensure high data accuracy and to derive actionable insights from complex datasets.
  • Communication and Visualization: Effective communication skills to translate data findings into clear reports and visualizations, making insights accessible for non-technical stakeholders.
  • Experience with Data Tools: Experience with data visualization tools like Tableau, Power BI, or Google Data Studio, and familiarity with database management systems for data organization and retrieval.



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