Associate Data Scientist

Overview

Cadent ignites seamless connections between brands, publishers & consumers. Our predictive AI orchestrates outcomes on any platform customers are on, across any media they consume & at any stage of the journey. To learn more, please visit thenewcadent.com.

Right now, we are looking for a highly motivated Associate Data Scientist who will be responsible for applying scientific methods to identify business optimization strategies and develop, evaluate and demonstrate prototypes of empirical software including but not limited to machine learning, signal processing and optimization based numerical methods.

Data Scientists collaborate directly with the Business, Product, Data Engineering, and QA team members to productize AI/ML research to drive business growth. This is a critical role that needs knowledge of mathematics and engineering, output from this role will be leveraged by business, engineers and by senior executives to define the future of Cadent.

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
• Follow the CRISP-DM process to generate robust documentation associated with iterative work
• Present results and findings to technical audience, product and business stakeholders
• Collaborate effectively with other members of the data science team, engineering research team and broader data services group including but not limited to Machine Learning Engineers, Data Engineers, Analytics Engineers, Software Engineers, Quality Assurance Engineers, and Business Intelligence analysts
• Participate in researching new data, tools, algorithms and tech stack to align with evolving AI & ML industry

Qualifications

• M.S. or higher in computer science, mathematics, or related discipline with a focus on machine learning; or the equivalent of 1-2 years’ experience in a similar role
• Proven background answering open ended research questions using data, tools and technology
• Ability to write clean, expressive code in Python and/or other tools including PySpark, Scala etc.
• Practical experience building, fine tuning and evaluating machine learning models, preferably with the scikit- learn ecosystem
• Experience with SQL and reading/writing from/to relational databases
• Experience using cloud computing ecosystems (e.g., AWS, GCP) is a plus
• Experience with the practical application of computational statistics
• Fundamental understanding of the mathematical workings of standard feature engineering, dimension reduction, machine learning algorithms and model validation & measurement
• Demonstrated communication skills including the ability to switch between technical and business contexts
• Familiarity with best practices for software engineering and the use of the scientific Python ecosystem
• Knowledge of GenAI tools and capabilities is a plus

Pay Range