Data from Second Measure drives core strategic decisions for our clients: how to invest multi-billion dollar portfolios, how to allocate nine-figure marketing budgets, and how to prioritize large partnerships and acquisitions.
Through our platform, our clients get instant visibility into any consumer company — how quickly they’re growing, whether they’re gaining or losing share in key markets, how well they retain customers, how much those customers spend over their lifetime, and even where else those customers shop.
This is game-changing data they have never seen before. For many, this represents a new and unfamiliar way of thinking about market research and the questions that could be answered.
This is where Data Services comes in. We’re a multi-disciplinary team focused on applying our data to real-world cases. We work directly with clients on their most significant strategic decisions. We translate their questions into testable hypotheses and address them with original research—novel models, analyses, and visualizations.
In this role, you’ll:
- Help clients answer real-world questions and guide them on how to use our data.
- Develop novel methods to address real-world questions. For example:
- Is HelloFresh growing the overall meal-kit market, or simply stealing customers from its competitors?
- When customers stop dining at Chipotle, where do they eat instead?
- How much more likely is an Equinox customer in San Francisco to shop at Lululemon, as compared with the average resident?
- Design, prototype, and deliver original analyses.
- Lead and/or participate in method reviews.
- You have a PhD in a quantitative discipline and/or years of experience as a data scientist.
- You’re an expert in applied statistics.
- You have experience teaching or communicating complex statistics to lay/general and technical audiences.
- You’re proficient in statistical computing.
- You have expertise in panel data, behavioral analysis, text processing, geolocation, and/or time series analysis.
- You have experience in large-scale, data-rich environments.
- You’ve built things with Python/Scala, Spark, Jupyter, Redshift/Hive, Athena/Presto, GPUs/TPUs, and/or D3 (and related).