SR. Data Analyst

Job Title: Sr. Data Analyst - Data Analysis
Job description:
Experience required: 5-7 years
Job Title: Sr. Data Analyst - Data Analysis
Job description:

Experience required: 5-7 years

• Consultant Primary Market Research
• Quantitative Primary Market Research
• Design and execute advanced quantitative PMR studies, including ATUs, demand estimation, segmentation, conjoint / discrete choice modeling, MaxDiff, message testing, concept testing, and brand tracking studies.
• Translate business objectives into robust survey instruments, including screener logic, quota design, rating / ranking scales, trade-off exercises, patient chart modules, allocation exercises, and analysis-ready question structures.
• Develop detailed analysis plans covering cross-tabs, statistical significance testing, derived importance, key driver analysis, segmentation profiling, respondent-level modeling, preference share estimation, and sensitivity analyses.
• Oversee data quality and analytical rigor across fielding and reporting, including sample validation, straight-liner / speeder checks, outlier review, weighting, data QC, and interpretation of statistically meaningful findings.
• Qualitative Primary Market Research
• Design and execute qualitative PMR studies, including IDIs, focus groups, advisory boards, online communities, ethnographic research, patient journey research, and hybrid qual-quant research designs.
• Develop technically sound discussion guides with structured probes, laddering techniques, behavioral elicitation methods, stimulus testing, concept exposure, message diagnostics, and decision-driver exploration.
• Analyze interview transcripts and notes using structured coding frameworks, thematic analysis, respondent archetyping, journey mapping, decision pathway mapping, and unmet-need identification.
• Synthesize qualitative findings into evidence-backed insights, distinguishing stated responses from underlying beliefs, motivations, barriers, emotional drivers, and behavioral triggers.
• Research Tools, Analytics, and Technology
• Use analytics and statistical tools such as Excel, Q, or equivalent platforms for data cleaning, analysis, visualization, and advanced modeling.
• Apply advanced research analytics including conjoint modeling, MaxDiff analysis, TURF, clustering, factor analysis, regression modeling

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