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Senior Data Scientist, Platform Insights (Remote)

N3TWORK is a Full Stack Games company – one that creates its own games and also builds technology and services for other gamemakers. Our flagship title Legendary, has generated over $250m in lifetime revenue and sets the standard for Live Events in mobile free-to-play games. We’ve also launched a version of Tetris to the world, along with Funko Pop! Blitz. These games are built on top of the N3TWORK Scale Platform (NSP) which enables us to invest hundreds of millions of mobile marketing dollars to achieve some of the highest ROI and LTV in the industry. NSP is now available to all developers to help grow their games and their businesses.

N3TWORK is headquartered in San Francisco, but is a fully distributed company. So, geographic location in the world is much less relevant to us than your drive and experience. We’re backed by some of the biggest names in venture & technology and we’ve assembled a great team of experienced and energetic N3TWORKers. Are you the next incredible addition to our company?

As a Senior Data Scientist working on Platform Insights, your ultimate goal will be to generate high quality insights about games we publish (or games that are candidates for publishing). Through your deep understanding of our business engine, combined with your analytical and statistical capabilities, you will synthesize data, product, and marketing insights together into tangible actions and partner with the Platform and Marketing teams to drive inflective outcomes.

You will be accountable for ensuring that we publish scalable games in the first place through market research and quantitative analysis of our marketing tests. Once we publish them, you will help our platform and marketing teams scale those games to their full potential while meeting ROI goals, by helping them understand gaps in performance and the causal impact of their actions over time.

The Ideal Candidate

• You are a competent storyteller, effective and uninhibited in communicating actionable insights to stakeholders. You are willing to engage in spirited dialogue about the findings, where you have to defend your methodology and interpretation.
• You are a competent statistician. You are capable of taking ownership of daily tasks such as generating predictions using various machine learning technologies, running MCMC simulations, or evaluating multivariate tests. You are well-versed in causal inference methodologies such as propensity score matching and regression discontinuity and know when to use them. You can tell a good instrumental variable from a bad one.
• You are a competent programmer, preferably in Python or R, fluent in SQL, and are familiar with distributed technologies (e.g. Spark). You have a spirit for aggressively automating away repeating tasks. You are capable of driving this process of automation and building utility tools for yourself and the rest of the team, while generating minimal requirements for our data engineering team.
• You are a competent scientist. Your specific background doesn’t matter nearly as much as the fact that you understand the scientific process and think deeply about causality. You generate and test causal hypotheses rigorously and robustly. You don’t jump to conclusions or confuse correlation with causation.

Roles and Responsibilities

• You will work directly with platform and marketing leaders and perform planned and exploratory analyses to provide actionable insights that drive horizontal and vertical growth as we continuously add games to our publishing business and scale them.
• You will help design experiments (A/B or multivariate tests) and will help maintain the technical and statistical aspects of our experimentation pipelines.
• You will work with massive amounts of raw data to create data visualizations and dashboards to surface trends, distributions, and relationships between business metrics.
• You will build, test, and deploy models for predicting and simulating business outcomes.
• You will ensure that at every step of the way, we make the best possible quantitative assumptions for modeling business outcomes before making decisions and navigate uncertainty with statistical rigor.