Quantitative Market Research Analyst

Ipsos; Chicago (IL); Híbrido; USD 65 000 - 90 000; Tempo integral

Resumo da oferta

Ipsos is seeking a Market Research Analyst to support the Innovation GMU with strong quantitative skills for statistical modeling and experimental research. You will design and analyze data-based studies, using tools like R, Python, SAS, SPSS, and Excel, and help translate results into client-ready insights.

The role involves data cleaning, coding, automation, and presenting findings to non-technical stakeholders in a collaborative, hybrid environment.

Qualificações

• BS or MS in Statistics, Applied Statistics, Biostatistics, Econometrics, or a closely related quantitative field.
• Strong foundation in experimental design, hypothesis testing, regression, ANOVA, and multivariate analysis.
• Experience designing and analyzing market research studies, including surveys and pricing research.
• Ability to design experiments and quasi-experiments to measure causal impact.
• Experience applying statistical methods to business decisions and communicating findings to stakeholders.

Responsabilidades

• Clean, structure, code, and summarize survey and secondary data.
• Use statistical software (R, SPSS, SAS) and Excel to run analyses.
• Apply programming (Python, Excel VBA) to automate standard procedures and chart creation.
• Translate analytic results into actionable client insights and recommendations.
• Deliver error-free work on time and with clear documentation.

Conhecimentos

Statistical modeling

Experimental design

Multivariate analysis

Hypothesis testing

Regression analysis

DOE

A/B testing

R

Python

SAS

SPSS

Excel

Survey design

Formação académica

BS or MS in Statistics, Applied Statistics, Biostatistics, Econometrics, Quantitative Psychology

Ferramentas

R

Python

SAS

SPSS

Excel

Descrição da oferta de emprego

Ipsos is seeking a Market Research Analyst to support the Innovation GMU with strong quantitative skills for statistical modeling and experimental research. You will design and analyze data-based studies, using tools like R, Python, SAS, SPSS, and Excel, and help translate results into client-ready insights.

The role involves data cleaning, coding, automation, and presenting findings to non-technical stakeholders in a collaborative, hybrid environment.