Horizon Commerce is looking for a data scientist to work on client-related services in the area of creative experience analytics, with the goal of eventually transitioning these capabilities into their NEON product. The role involves developing and optimizing marketing data science models, analyzing user behavior, and driving business outcomes through data-driven insights.
Requirements
- At least 7 years experience in Machine Learning client analytics role
- 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 of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, computer vision techniques, etc.) and their real-world advantages/drawbacks.
- Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
- Prior experience working at a marketing agency and/or a consulting firm on a marketing data science, advanced analytics development, and/or user behavior or engagement team is required.
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.
- Demonstrated ability to extract business insights from large datasets and use them to drive business change
- 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.
- Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
Other
- Experience in working with client services teams and communicating technical findings directly with client technical team members.
- Domain expertise in the area of creative analytics and creative and/or conversion rate optimization strategies
- Proven experience to interact in a collaborative fashion with Product Management from analytic conceptualization, through hands on exploratory data analysis (EDA), piloting and production rollout within performant backend APIs
- Independently motivated to conceptualize and execute proactive client analysis
- Communication skills and an ability to collaborate with clients
