Horizon Commerce is looking to solve the problem of helping advertisers gain a better understanding of the changing eCommerce landscape and ignite innovation around ways to plan, manage, and optimize eCommerce media.
Requirements
- Deep expertise in Python (and libraries), R, SQL
- Ability to operate in Snowflake, AWS infrastructure of S3/EC2, etc
- Existing skill sets in machine learning, computer vision and product development
- Familiarity with a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, computer vision techniques, etc.)
- Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.)
- Experience with applications of machine learning and statistical techniques
- Ability to work with large datasets and extract business insights
Responsibilities
- Create and elevate current analytics methodology, build a replicable statistical framework, within the constructs of a composable analytics framework and the NEON platform
- Model outputs and inputs, working with the Data Engineering team to assure data processes are automated and efficient
- Incorporate multiple 3rd party APIs & other datasets from different sources, into one (or more) custom-developed measurement and display systems.
- Mine, aggregate and analyze data from databases to drive optimization and improvement
- Familiarity of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, computer vision techniques, etc.) and their real-world advantages/drawbacks.
- Help build and validate requirements and use cases between the core NEON team and the CX team.
- Evaluate external AI solutions for their modeling and predictive strength, that may be pertinent to the CX use cases to complement NEON featureset in addition to ones being built in the ensemble of models.
Other
- At least 7 years experience in Machine Learning client analytics role
- Experience in working with client services teams and communicating technical findings directly with client technical team members.
- Hold an undergraduate degree in math, statistics, computer science or other technical degree
- Superb problem synthesis and communication skills
- Keen attention to detail and data integrity
- Ability to collaborate with clients and communicate technical findings effectively
