Responsibilities of the Candidate:

• Partner with internal stakeholders to understand the research objectives and hypothesis; and provide data-related support on the same. 
• Assist in the creation of primary data collection instruments (surveys, web data, etc.), questionnaires, the study scope, sampling methodologies, and analytical techniques to test hypotheses and calibrate data models.
• Employ analytical tools to analyze survey data, and correlation between survey responses and client engagement in a meaningful way to result in actionable insights.
• Assist with large-scale data collection efforts through the administration of data through the process and managing the quality of the same.
• Tell the primary research data story through analysis, interpretation, and data visualization that clearly conveys key takeaways using Powerpoint or other data visualization tools. Support insightful graphics, user-friendly data tables, and simple dashboards to communicate findings.
• Present analytical insights and research findings through benchmarks, member summary reports, and other standardized reports to clients and internal research teams.
• Exploring and implementing new tools and features to improve the quality of deliverables and efficiency in the process.
• Work with and support team members to assist in maintaining the quality of the data and deliverables based on the same by managing through a robust quality check process.
• Manage aspects of Data operations through ETL, data modeling, and data automation activities.

Requirements:

• 0 - 2 years of Market Research industry experience working with one or various data applications such as SPSS, Q, SAS, etc.
• Understanding and proficiency in data tables, graphs, and charting techniques.
• Good understanding of data & statistical techniques, analytical mindset, and ability to learn new tools and techniques quickly.
• Experience in business analytics and visualization tools such as Power BI, QlikView, Tableau, etc. would be a plus.
• Knowledge and experience of programming languages such as Python or R
• Familiarity with survey programming and programming languages such as JavaScript, jQuery, HTML, and CSS would be an added advantage.
• Familiarity with data modeling techniques, including regression analysis, natural language processing (NLP), and machine learning (ML).