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Data Analyst Data Engineer Data Science Manager Data Mining

Power BI Developer Data Science

Job in Richmond, Henrico County, Virginia, 23214, USA
Listing for: TechDigital Group
Full Time position
Listed on 2025-11-25
Job specializations:
  • IT/Tech
    Data Analyst, Data Engineer, Data Science Manager, Data Mining
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Position: Power BI Developer with Data Science

Qualifications:

  • 5+ years of expertise in creating interactive and visually appealing dashboards and reports using Power BI. Proficiency in designing and developing Power BI Paginated Reports.
  • 3+ years of experience with data warehousing concepts and ETL processes.
  • Experience in Power BI administration is a plus.
  • Strong understanding of statistical concepts, machine learning algorithms (e.g., regression, classification, clustering), and data mining techniques.
  • Proficiency in Python, SQL, and DAX. Experience with other programming languages (e.g., R) is a plus.
    • Responsibilities:

    Power BI Development:
  • Design and develop interactive and visually appealing Power BI dashboards and reports.
  • Design and develop professional-grade Power BI Paginated Reports.
  • Create DAX measures and calculations for complex data analysis.
  • Integrate data from various sources into Power BI models.
  • Optimize Power BI reports for performance and scalability.
  • Develop and maintain data pipelines and ETL processes.
  • Effectively communicate data insights to business stakeholders through presentations, reports, and visualizations.
  • Collaborate with business users to understand their data needs and translate them into actionable insights.
  • Provide data-driven recommendations to improve business processes and decision-making.
    • Data Analysis & Modeling:
  • Collect, clean, and transform raw data from various sources (e.g., databases, APIs, cloud platforms) using SQL, Python, and other data manipulation tools.
  • Conduct exploratory data analysis (EDA) to identify trends, patterns, and anomalies.
  • Develop and implement predictive models (e.g., regression, classification, clustering) using machine learning algorithms.
  • Perform statistical analysis and data visualization to uncover meaningful insights.
    • #J-18808-Ljbffr
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