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Full-stack Behavioural Scientist: a complete guide

Updated: Dec 8, 2023

Behavioural Science is a relatively new and constantly evolving interdisciplinary field. This novelty creates unique challenges for both aspiring behavioural scientists and those seeking to hire them. I notice two specific pain points in this field:

  • Aspiring and early-stage Behavioural Scientists struggle to identify the essential skills and knowledge needed due to the field's interdisciplinary nature. It's challenging to understand which skills are crucial and which are less relevant.

  • Hiring Managers, often not specialists in Behavioural Science themselves, often struggle to identify the essential skills in potential candidates. Roles in behavioural science are often broadly defined, leading to a misconception that one must always be a 'full stack' behavioural scientist, proficient in all aspects of the field.

This guide aims to provide a structured roadmap for individuals entering behavioural science and for organisations looking to build robust behavioural science teams.

The concept of 'stacks' in behavioural science mirrors that in technology – it refers to a set of skills or knowledge areas necessary for proficiency in the field. Here, we discuss the four key stacks: the Foundational Stack, the Research Stack, the Application Stack, and the Impact Assessment Stack. Skills like communication, reporting, intuition, and efficient learning are also crucial, but since it’s common across various fields and job roles, we will not be diving into that.

The different stacks in Behavioural Science
The different stacks in Behavioural Science

I. The Foundational Stack

The foundational stack forms the essential bedrock of one's capabilities in behavioural science. It understanding of psychology, sociology, anthropology, microeconomics, cognitive science, neuroscience, social psychology, ethnology, game theory, experimentation, and more. That sounds like a lot but these fields are heavily interconnected and a behavioural scientist needs it all to be effective.

For example, when examining phenomena such as the bystander effect, a good behavioural scientist with a strong Foundational Stack would consider psychological factors like diffusion of responsibility, sociocultural influences such as prevailing social norms, and biological aspects like the fight-or-flight response.

The Foundational Stack
The Foundational Stack: the bedrock of BehSci

For Learners: How do you build your Foundational Stack?

To excel in the foundational stack, immerse yourself in all these fields.

  • Educational Pursuits: Engage deeply with textbooks and foundational research papers

  • Academic Engagement: Actively participate in seminars and academic discussions to broaden and challenge your understanding.

  • The Brain Capsules: This is a weekly series, where we make Behavioural Science principles short, sweet, and easy to digest - shared on our social media pages every week (Instagram | LinkedIn | Twitter)

For Hiring Mangers: How do you evaluate Foundational skills

II. The Research Stack

The research stack is essential and here, one gets to pick and choose what they would like to specialise in. In the research stack, we include the methods and techniques with which one approaches a problem, collects and analyses the relevant information. We break this further into 3 sub-stacks - qualitative, quantitative and theoretical. If you are an expert on a combination of these and know how to apply them together to build a narrative, you will be called a mixed-methods person.

The Research Stack: Qualitative, Quantitative and Theoretical
The Research Stack: Qualitative, Quantitative and Theoretical

The Qualitative Research Stack

Qualitative research employs a variety of methods to gather in-depth understanding of human behaviour, experiences, and the reasons that govern such behaviour. The qualitative methodology is primarily exploratory, aimed at gaining insights and understanding of underlying reasons and motivations. This includes a variety of methods like interviews, focus groups, observation, ethnography, case studies, content analysis, narrative analysis, grounded theory, phenomenology, and discourse analysis.

The Quantitative Research Stack

Quantitative research methods are used to collect and analyse data in a structured and statistical manner. By emphasising quantifiable variables and statistical relationships, quantitative research aims to draw definitive conclusions and establish cause-and-effect relationships. To excel in this field, it's crucial to understand and adeptly apply various quantitative research methods encompassing data collection using surveys, experiments, etc and statistical data analysis including longitudinal and cross-sectional studies, panel studies, path analysis, factor analysis, and correlation/ causation studies. Pick up some basic SQL and data analysis tools/languages such as Python or R.

The Theoretical Research Stack

Theoretical research involves the systematic exploration of abstract concepts, models, and frameworks to develop, refine, or challenge theoretical understandings. Unlike empirical research, which relies on observable and measurable data, theoretical research primarily operates in the realm of ideas, engaging with hypotheses, concepts, and existing theories. This type of research often involves critical analysis, synthesis of existing knowledge, and the construction of new theoretical frameworks. To excel in this, one needs to get comfortable with conceptual analysis, model building, simulations, historical analysis, literature reviews, philosophical inquiry, comparative analysis, and logical analysis.

III. The Application Stack

This stack is all about learning to apply the theories you’ve learnt in real-world contexts. Unlike the foundational stack, excelling in this stack is very much an individual-process that requires a lot of practice.

A good behavioural scientist needs to specialise further here. For instance, you can delve into the development sector or policy framing. Or, you can learn the tricks of trade in business and specialise in strategy, product, UX design or even finance or HR. Pick a domain and deep dive - learn the jargons, skills and strategies. And then practice to apply behavioural science there!

The Application stack: Your domain-specialisation
The Application stack: Your domain-specialisation

For Learners: How to get good with the Application Stack?

  • Hands-On Experience: Take up independent research projects, or domain-specific training/internship.

  • Nudgeathons: Nudgeathons are a great place to learn how to apply the foundational theory in real-world scenarios. Take part in many Nudgeathons!

  • Applied Research: Read applied research papers and case studies for practical insights.

For Hiring Mangers: How you can assess Application skills?

IV. The Impact Assessment Stack

Impact assessment in behavioural science is a critical process that measures the effectiveness and outcomes of interventions, policies, or programs. It's a vital component for professionals in this field, as it validates the practical application of theoretical knowledge and research.

Train yourself to be proficient in selecting appropriate methodologies for impact assessment, along with a thorough understanding of statistical techniques and the ability to conduct basic data analysis

The Impact Assessment Stack
The Impact Assessment Stack

For Learners: How do you expand your Impact Assessment skills?

  • Educational Pursuits: Advanced courses in statistics, research methods, and program evaluation can deepen your understanding.

  • Practical Experience: Engaging in real-world impact assessments through internships, projects, or collaboration with research teams.

For Hiring Mangers: How can you assess Impact Assessment ability?

Categorising Behavioural Scientists: Exploring Expertise through Stacks

Behavioural scientists can be classified into various types based on their expertise in the different stacks outlined. Each category contributes a unique set of skills and perspectives to the fiekd:

  • Qualitative Behavioural Scientists primarily use qualitative methods in their research. Their expertise lies in understanding the depth and complexity of human behaviour using methods such as interviews, focus groups, and ethnography. Their strength lies in capturing the nuances of human experience, offering rich, detailed insights that are often missed in quantitative analysis.

  • Quantitative Behavioural Scientists primarily use data and various qualitative methods for their research. They use structured methods like surveys, experiments, and statistical analysis to collect and interpret data. Their work typically involves a more numerical and objective outlook, offering a comprehensive view of behavioural patterns.

  • Theorist Behavioural Scientists focus on developing and refining behavioural models and theories. These scientists work to enhance our conceptual understanding of behavioural phenomena, often drawing on philosophical inquiry, comparative analysis, and logical reasoning. Their contribution is crucial in providing a foundation for both qualitative and quantitative research as their work is less about direct data collection and more about the synthesis of existing knowledge to create comprehensive theories about human behaviour.

  • Mixed-Methods Behavioural Scientists demonstrate versatility in both qualitative and quantitative research methods. They integrate both approaches to gain a holistic understanding of behavioural issues, making them particularly valuable in research where both depth and breadth of information are needed.

  • Domain-Specific Behavioural Scientists specialise in applying behavioural science principles within a specific domain, such as finance, healthcare, or public policy. They are proficient in the Application Stack, using their expertise to design interventions and strategies tailored to their area of specialisation.

  • Full-Stack Behavioural Scientists - akin to a full-stack developer in the tech industry - is a highly skilled professional who is proficient in all the stacks: Foundational, Research (both qualitative, quantitative and theory), Application across various domains, and Impact Assessment. They provide a comprehensive approach to behavioural science, capable of addressing issues in various domains using multitude of research methods.

To sum up...

The field of Behavioural Science is diverse and complex, requiring a multifaceted skill set that spans various disciplines and methodologies. By understanding the four key stacks - Foundational, Research, Application, and Impact Assessment - aspiring and established behavioural scientists can better navigate their career paths and enhance their expertise. Similarly, hiring managers can use this framework to identify and evaluate the necessary skills in potential candidates.

  • For Aspiring Behavioural Scientists: This guide serves as a roadmap for acquiring and honing the skills necessary to thrive in this field. It emphasises the importance of a strong foundation in various social and behavioural sciences, a deep understanding of research methodologies, the ability to apply theories in real-world scenarios, and the skills to assess the impact of interventions.

  • For Hiring Managers and Organisations: This framework offers a structured approach to identifying key competencies in behavioural science candidates. It helps in recognising the specific strengths and expertise of individuals, whether they are more aligned with qualitative or quantitative research, theory development, application in specific domains, or a combination of these areas.

Ultimately, the field of Behavioural Science benefits from a diverse range of professionals who bring different perspectives and skills. Whether one specialises in a single stack or develops a full-stack expertise, their contributions are vital in advancing our understanding of human behaviour and designing effective interventions to improve various aspects of society and business.


 

This article was contributed by Junofy Anto Rozarina.


Junofy is a renowned Behavioural Scientist who serves as the CEO of Beyond Nudge, a global behavioural science consultancy company. She is also the founder and CEO of India Behavioural Economics Network (IBEN) and sits on expert boards of various organisations. She’s a seasoned practitioner, researcher and public speaker with a strong passion for deciphering the intricacies of human cognition and decision-making processes. Over the years, she has worked with several organisations including Google, Swiggy, UNICEF and UNDP, and has delivered lectures at forums, universities and organisations around the globe.


December 2023

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