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Princeton, NJ · Information Technology
 Our client, a leading Technology Services firm, is seeking a Data/Business Analyst for their cutting-edge Digital Solutions Group.  This role is based in Princeton NJ, with one day per week onsite at their office and four days remote.  

We are looking for a Senior Data/Business Analyst to make sense of our performance of digital solutions and capabilities using advanced analysis to identify meaningful and actionable insights - advancing performance and promoting a culture of data-driven decision making.  In this role the Senior Data/Business Analyst will support the Digital Solutions Organization in producing valuable insights, building reports and dashboards, and conducting analysis in support of ongoing projects and strategic initiatives. The Senior Data/Business Analyst will work closely with our Product and Capability Owners to become familiar with our offerings and work to define data requirements, KPIs, and actionable metrics that can demonstrate the value of our solutions to our customers and help drive strategic business decisions. The Senior Data/Business Analyst should have advanced skills in data visualization tools, data analysis, and business analysis. The Senior Business Analyst should be comfortable owning and leading project activities as required and be able to independently build high quality products and relationships. 

Essential Job Duties
  • Supports the Digital product owners in defining the BI and analytics product vision, goals and strategy and communicate those to stakeholders, including project business owners, clients, development team and other internal system owners.
  • Function as point of contact for data and analytical usage across multiple capabilities, and guide partners on product performance and solution improvement/maturity options.
  • Analyze extracted data, identify trends and provide insights and analyses around Digital and project data.
  • Design, develop and implement new metrics, functions, and scripts as KPIs and in existing BI/Dashboards as needed.
  • Ad hoc tool development to support operational and underserved analytical areas.
  • Apply advanced methods to analyze Digital solutions data and derive meaningful, actionable insights for stakeholders and business development partners
  • Serve as subject matter expert (SME) in the area of data and analytical product usage for peer analysts and operational stakeholders – particularly in the appropriate uses and limitations of statistical and analytical applications
  • Inform operational partners on product performance as well as product usage trends
  • Consult with analytical leaders to understand current and future business goals and strategies, and ensure that methods and work products are aligned
  • Balance accuracy of analysis with needs for rapid response
  • Develop partnerships with technical peers and business partners
  • Project Management activities

Education and Experience Requirements
  • BS in a quantitative field such as Statistics, Mathematics, Management Information Systems (MIS), Economics, Computer Science, Business Analytics, or related quantitative field
  • Advanced degree in Computer Science, Mathematics, Information Systems, Business Analytics, MIS, Engineering, or a related technical field preferred.
  • 5+ years of experience performing quantitative data analysis and business analysis
  • 5+ years of experience with data visualization and business intelligence tools or packages (SSRS, Power BI, Tableau, MicroStrategy, etc.) with ability to lead and train on best practices of BI use.
  • 5+ years of experience quantifying and prioritizing projects that require heavy data analysis
  • 5+ years of experience working directly with business users and requirements documentation
  • Ability to present data in a simple, clean, concise visual and written manner
  • Statistical experience and understanding of distributions, statistical testing, regression, etc.
  • A strong passion for empirical research and for answering complex questions with data
  • Experience with solution/vendor evaluation and evaluating product ROI
  • Exposure to machine learning techniques and algorithms
  • Exposure to (or strong desire to learn) common data science toolkits, such as R, Weka, Python/NumPy, etc

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