About The Position

NIQ is a consumer intelligence company that provides data and analytics to help organizations understand consumer buying behavior and identify growth opportunities. The Financial Services Data Research Team supports the global investment community with datasets, research, and analytical expertise. Its clients include hedge funds, mutual funds, pension funds, and quantitative investment firms. The position serves as a subject matter expert on NIQ’s financial services datasets, working directly with clients to help them understand, evaluate, and use the data. It combines advanced analytics, statistical modeling, client engagement, and financial market knowledge, and contributes to client success, product adoption, and business growth. The role works with Product, Data Science, Technology, Commercial, and Client Success teams to improve existing data products and develop new solutions.

Requirements

  • Bachelor’s degree in Statistics, Engineering, Economics, Finance, Mathematics, or another highly quantitative discipline.
  • Professional experience in Analytics, Research, Financial Services, Consulting, Data Science, or a related field.
  • Applied statistical expertise, including regression analysis, statistical inference, data imputation, and time-series analysis.
  • Proficiency in Python, R, SAS, or MATLAB.
  • Strong SQL skills and experience working with relational databases.
  • Advanced Microsoft Excel capabilities.
  • Ability to transform large and complex datasets into actionable business insights.
  • Excellent verbal, written, and presentation skills, including the ability to communicate effectively with sophisticated client audiences.
  • Strong organizational, planning, and project management skills.
  • Ability to thrive in a fast-paced, collaborative, client-facing environment.

Nice To Haves

  • Experience in asset management, hedge funds, mutual funds, pension funds, or quantitative investment environments.
  • Consulting, investment research, or financial analytics experience.
  • Familiarity with e-commerce, consumer, retail, or alternative datasets.
  • MBA or a master’s degree in Financial Mathematics, Statistics, Economics, or a related field.
  • Experience building quantitative models that inform investment decisions.
  • Strong understanding of capital markets, investment strategies, and macroeconomic drivers.
  • Curiosity and enthusiasm for learning analytical methodologies, technologies, and financial market concepts.

Responsibilities

  • Serve as a primary point of contact for clients using NIQ financial services datasets, providing expert guidance and analytical support.
  • Support data trials and proof-of-concept initiatives for prospective and existing clients evaluating datasets.
  • Discuss data methodologies, data quality, and investment applications with clients.
  • Develop statistical analyses and quantitative models to identify trends, patterns, and signals in large datasets.
  • Analyze drivers of company and sector performance and connect them to insights from NIQ e-commerce and consumer datasets.
  • Create client-facing research, presentations, and analytical materials that translate complex data into actionable investment insights.
  • Collaborate with Product, Data Science, Technology, Commercial, and Client Success teams to enhance existing data products and develop new solutions.
  • Identify opportunities to improve data coverage, methodologies, and analytical frameworks for investment clients.
  • Stay informed about financial markets, investment trends, and emerging analytical techniques.

Benefits

  • Flexible working environment
  • Comprehensive healthcare plan, including medical, prescription, dental, and vision coverage
  • Flexible spending accounts and a Health Savings Account, including company contributions
  • Life and AD&D insurance
  • 401(k) retirement plan with company matching contributions
  • Disability insurance
  • Tuition reimbursement and education support
  • Discretionary paid time off
  • 11 paid holidays
  • Volunteer time off
  • LinkedIn Learning
  • Employee Assistance Program
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