J.P. Morgan's Corporate & Investment Bank (CIB) is a leader across banking, markets and investor services. The world's most important corporations, governments and institutions entrust us with their business in more than a hundred countries.
Digital Experience Design, our global CIB design team of 125+ designers in 7 locations plays a key role in building customer-centric products and services for both clients and employees.
Do you want to improve client experience at scale by measuring the behaviours, beliefs, and attitudes of Corporate and Investment Banking clients? We are looking for a creative, resourceful, and organized Behavioural Research Scientist in Digital Experience Design’s Client Experience Measurement team.
Part of Corporate and Investment Banking, the Digital Experience Design organization’s mission is to improve the experience of external clients and internal users across a broad variety of complex, essential, and high-value product and service journeys. The Client Experience Measurement program contributes to this mission using quantitative research to provide the data required to make key design and investment decisions.
As a quantitative behavioural researcher, you will work closely across design, product, and technology teams to better understand our clients. You will be asked to help partners develop meaningful and relevant research questions, and in answering those questions with a variety of input data sources, to deliver concrete, actionable client experience recommendations. In addition to analysing data to answer individual research questions, you must be able to connect data with design decisions, collaborating closely to ensure the relevance and impact of your work to business stakeholders.
You will be expected to be a subject matter expert in measurement and quantitative analysis of behavioural and/or survey response data, with the ability to communicate highly complex findings to multiple audiences. You may come from one of a variety of backgrounds (e.g. psychology, HCI, economics, epidemiology, among others) but you must be comfortable with the complete research workflow, from research design to statistical analysis to reporting, and you must have some experience with quantitative behavioural and/or attitudinal data.
Successful candidates will take iterative approaches to tackling big, long-term problems and show the ability to apply expertise in social science methodology, earn trust with partner teams from non-statistical backgrounds, understand the right level of statistical complexity to fit the research questions and existing resource constraints, be willing to experiment and learn from what works, and communicate scientific approaches to a variety of stakeholders.
- Provide expertise in applied social science research
- Partner with a variety of teams to:
o collaboratively identify client experience outcomes and key research questions
o make methodological recommendations for data collection and analysis
o develop and execute statistical analysis plans to answer key questions across multiple data sources
o make recommendations for design based on quantitative analysis results
- Contribute to scalable process recommendations to build a larger culture of data-driven decision-making
- Lead a team of quantitative researchers, to achieve team and program goals
- MS in a quantitative social science discipline (e.g. psychology, economics, HCI, learning science, sociology, epidemiology)
- Significant experience conducting large-scale applied research including analysis of human behaviour and/or survey data
- Advanced statistics (factor analysis, SEM, causal modelling, multilevel regression, regularized regression, etc.) – although we don’t expect candidates to have expertise across methods, the successful candidate should be fluent with at least two methods and be comfortable acquiring new methods with training and practice
- Proficiency in at least one statistics program (Python, SPSS, R, SAS), Python strongly preferred
- PhD in a quantitative social science discipline (e.g. psychology, economics, HCI, learning science, sociology, epidemiology)
- Experiences with SQL or related query languages, data management, data warehousing
- Experience converting research studies into tangible, real-world changes
- Experience communicating complex technical information for non-technical audience