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AI Assistant for your digital marketing

Machine Learning & Data Science Engineer

$20k – $40k • 0.25% – 0.75%
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Glance is building an intelligence layer for marketing technology. You will be joining a team of ambitious folks (ex MIT, Citrix, Adnuance) who have extensive experience founding an agency and running enterprise-level products. We believe in empowering marketers with the power of data science without them having to spend a fortune on this expertise.

Glance is the marketing AI assistant that collates multi-channel marketing data and surfaces hidden insights, opportunities and course corrections all in simple language allowing you to act on the insights from Glance.

If you’re the person who believes in leveraging AI/ML to democratize marketing, this is the right position for you. In this job you will:

- Create an overall schema to accommodate the insights generation aspect, to marketing channels (such as Google Analytics)
- Create AI models to organize data by paid and non-paid marketing channels
- Convert rules-based insights to model generated insights
- Incorporate causal models in campaigns and create remedial actions based on causes determined.
- Identify anomalies in marketing data and drive to insights where applicable
- Use data analysis skills and incorporate automatic insight creation from existing data

About You:

* Undergraduate/graduate degree in CS-related field OR significant professional experience
* Professional machine learning experience of 2.5+ years with a solid understanding of statistical methods
* Have good software engineering skills with ability to do some devops which include pushing applications to production
* We’d like a can-do attitude in the face of constraints and come up with creative solutions. Passion for learning, building, and moving fast.
* Ability to understand the current platform and existing tech infrastructure to build ML and data layers in a modular fashion
* Strong experience with high-level machine learning frameworks (Tensorflow, Caffe, Torch, etc.)
* You are capable of quickly coding and prototyping data pipelines involving any combination of Python, Node, bash, and linux command-line tools
* Comfortable with running and interpreting common statistical tests, and also with common data science techniques including dimensionality reduction and supervised and unsupervised learning