Research & Insights Manager

Grounded in a talent-centric mindset, Maker Lab is a marketing agency designed to build decentralised technology-led agency teams, rooted in collaboration with clients from the ground up. Maker Lab’s cross-functional teams of multidisciplinary specialists are embedded into client teams across digital marketing competencies — from measurement \& analytics to content production.

Senior Research \& Insights Manager

We are seeking a highly motivated and analytical individual to join us as a Senior working on casual interference and marketing effectiveness. In this role, you will play a crucial part in developing and documenting our approach to causal inference and causal machine learning (causal ML) initiatives.. You will leverage your understanding of data science principles and Ads products to contribute to internal resources, conduct in-depth analyses, and generate actionable insights that drive impactful marketing decisions.

Work closely with data scientist marketing effectiveness research managers and product teams such as GTMs to support and lead some modules in causal inference and ML research.

Role:

• Based on structures and frameworks created by Marketing Effectiveness Research Manager and GTMs, writing contents of the internal guidebook causal inference/ML applications for LCS clients, including 3rd party projects and in-house MMM support such as double-pipeline

• The content includes a technical step-by-step process description for managing casual ML modelling processes and supporting clients’ data scientists.

• While you do not have to be familiar with all domains in data science, you should be able to understand technical content in data science, including mathematical descriptions.

• Support causal inference/ML research modules led by Marketing Effectiveness Research Managers and data scientists to create proof points of empirical knowledge and algorithms. The research modules includes the following processes:

• Conducting EDA (Exploratory Data Analysis) to check data distribution, correlation and causal relation.

• Using basic statistical models such as statistical tests, decision tree, clustering, linear regression and logistic regression to consider causal relationships among data.
• Applying causal inference/ML models and frameworks to the data to estimate causal effect of treatments on business metrics to measure their performance.
• Designing simulated data with guidance of data scientists.
• Drawing charts and slides to explain the insights to the Marketing Effectiveness Research Manager data scientist and stakeholders where necessary.
• Supporting documentation based on the insights in the above process.

Please note: due to the high volume of applications, only successful candidates will be contacted with a follow-up introduction email. If you do not receive an email from Maker Lab, your application has been unsuccessful this time around. Look out for future roles! By submitting your application, you consent to the collection, use and disclosure of your data by the Maker Lab team for the purposes of your application. Where your application contains personal data of third parties, you confirm that you have obtained all necessary consents to provide the Maker Lab team with such personal data and that we may collect, use and/or disclose such data in accordance with the Personal Data Protection Act 2012.