Cadent is looking to solve business optimization strategies and develop prototypes of empirical software including machine learning, signal processing and optimization based numerical methods.
Requirements
- M.S. in Computer Science, Mathematics, Statistics, a related quantitative field, or equivalent practical experience with a focus on machine learning
- Ability to write clean, expressive code in Python and/or other tools including PySpark, Scala etc.
- Practical experience building and evaluating machine learning models, preferably with the scikit- learn ecosystem.
- Experience with SQL and reading from relational databases
- Experience using cloud computing ecosystems (e.g., AWS, GCP) is a plus
- Fundamental understanding of the mathematical workings of standard feature engineering, dimension reduction, machine learning algorithms and model validation & measurement
Responsibilities
- Design, train and apply statistics, mathematical models, and machine learning techniques to create scalable solutions to business problems
- Work with machine learning engineers and software developers to deploy models and modeling pipelines to be leveraged inside of business software products
- Contribute iterative improvements to predictive models
- Leverage model governance techniques and frameworks to ensure performance and stability of data science products
- Work with product team to align on product roadmap and goals with business vertical KPIs
- Participate in the Agile / scrum process
Other
- M.S. in Computer Science, Mathematics, Statistics, a related quantitative field, or equivalent practical experience with a focus on machine learning
- 1+ years professional experience in a similar role
- Demonstrated communication skills including the ability to switch between technical and business contexts
- Media or ad-tech experience a plus
