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Data Scientist, Marketing Measurement and Optimization R&D

LiftLab Company Overview

Digital marketing teams use LiftLab to uncover the economics of their ad platform partners including FB/Instagram, Google, Display, Snapchat, TikTok and Pinterest. They use these signals to make daily spending decisions with confidence. LiftLab customers know for each channel, tactic, campaign if the revenue for the last $1 spent covered its cost. LiftLab is built on a foundation of advanced algorithms and sophisticated media experimentation. Some of the most marquee brands already run LiftLab and we’re growing at a rapid pace.


Responsibilities

In this role you will be developing tools for analysts and automated code to analyze data and build structural models that will be used for insights generation and budget optimization. This is not primarily a role that analyzes specific datasets. It is important that you understand the statistical algorithms and optimization algorithms well enough to anticipate how they will behave across a wide range of datasets and how to make them robust enough to facilitate automation

  • Prototype and develop new algorithms and features for marketing experiment analysis, market response modeling, budget optimization

  • Enhance our current modeling, analysis and optimization backend

  • Work closely with Analysts, Customer Success Managers, Marketing Scientists to ensure relevance and applicability of the algorithms and to develop prioritizations

  • Work with engineering to incorporate new functionality into the LiftLab solution

  • Create documentation and teaching materials

  • Communicate methodology internally and externally

The ideal candidate will bring a passion for learning, an interest in how innovation can accelerate media investment decisions and a willingness to dive into new tools and systems.


Requirements

In this role you will be developing tools for analysts and automated code to analyze data and build structural models that will be used for insights generation and budget optimization. This is not primarily a role that analyzes specific datasets. It is important that you understand the statistical algorithms and optimization algorithms well enough to anticipate how they will behave across a wide range of datasets and how to make them robust enough to facilitate automation

  • Deep understanding of statistical techniques and principles of mathematical optimization

  • Demonstrated ability to translate real-world phenomena into structural mathematical representations (being able to model rather than just to apply an algorithm to a dataset)

  • Hands-on experience using R and Python, and SQL for data manipulation and statistical analysis

  • Ability to write well-structured and documented prototype code working on real client datasets

  • Ability to tolerate ambiguity dealing with messy data and striking a good balance between pragmatism and technical rigor

  • Strong ability to communicate technical concepts

  • Bachelor’s degree or higher in a quantitative field

  • Some industry experience in marketing analytics or related fields is desirable

  • Eligible to work in the US or Canada


Location

Fully remote, with normal work hours on US Mountain Time

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