Data Scientist with econometrics
We are looking for an experienced Data Scientist to join our team!
About the Role
Measure Protocol is a leading consumer behavioural data company servicing some of the world's largest brands and media companies as its clients.
Measure has been collecting behavioural data from consumers over several years and has a vast data asset.
The role of the Data Scientist will help shape and mould Measure’s approach and products to build the best-in-class consumer data company.
About Measure
Measure is building the world’s first ethical and transparent human data marketplace.
The world we live in is awash in data: what we watch and wear, who we know, what we do, and how we live our lives. Unfortunately, most of this data is owned and controlled by corporations and we have very little say in when and where it gets used, let alone being compensated for its use.
We have a bold mission with a lot of complexities, but we believe there is a real opportunity to change how we manage and monetize our data lives with more control, and in a way that benefits us personally, and as a society as a whole with better data-supported decisions.
Measure has recently raised investment from both venture capital and strategic firms.
Key Responsibilities:
Data Cleaning and Preparation:
Collect, clean, and prepare large media datasets from various sources (CRM, ad servers, audience panels) for analysis.
Statistical Analysis:
Utilize econometric techniques like regression analysis, time series modeling, and panel data analysis to identify relationships between media spend and business outcomes.
Model Validation and Interpretation:
Evaluate the accuracy and robustness of models, interpret results, and communicate findings to stakeholders in a clear and concise manner.
Campaign Optimization:
Provide data-driven insights to inform media buying strategies, including channel allocation, budget optimization, and creative testing.
Advanced Analytics:
Explore new data analysis techniques like machine learning to enhance model accuracy and uncover deeper insights.
Required Skills:
Strong Econometrics Background:
Expertise in statistical methods like linear regression, generalized linear models, panel data analysis, and time series forecasting.
Data Science Proficiency:
Proficient in programming languages like Python, R, and SQL including data manipulation, data imputation, statistical modeling, and visualization libraries.
Media Industry Knowledge:
Understanding of media landscape, ad formats, audience measurement, and industry KPIs.
Communication Skills:
Ability to clearly communicate complex statistical concepts and insights to non-technical stakeholders.
Business Acumen:
Understanding of business objectives and ability to translate data
insights into actionable strategies.
Additional Skills:
Marketing Mix Modeling (MMM):
Build and maintain complex MMM models to assess the incremental impact of different media channels (TV, digital, print) on sales, considering factors like seasonality and competition.
Campaign Optimization:
Provide data-driven insights to inform media buying strategies, including channel allocation, budget optimization, and creative testing.
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