Cadent is looking for a Data Scientist to apply scientific methods to identify business optimization strategies and develop, evaluate, and demonstrate prototypes of empirical software, including machine learning, signal processing, and optimization-based numerical methods. The goal is to productize AI/ML research to drive business growth and define the future of Cadent.
Requirements
- 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 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
- Experience with the practical application of computational statistics and complex ML algos including deep learning, GraphDB SVMs, time series forecasting etc. to build and evaluate models
- Knowledge of LLM technologies, including generative and embedding techniques, modern model architectures, retrieval-augmented generation (RAG), fine tuning / pre-training LLM (including parameter efficient fine-tuning), and evaluation benchmarks
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
- Follow the CRISP-DM process to generate robust documentation associated with iterative work
- Participate in researching new data, tools, algorithms and tech stack to align with evolving AI & ML industry
Other
- M.S. in Computer Science, Mathematics, Statistics, a related quantitative field, or equivalent practical experience with a focus on machine learning; or the equivalent of B.S with 2-3 years of experience in a similar role
- 1+ years professional experience in a similar role.
- Proven background answering open ended research questions using data, tools and technology
- Demonstrated communication skills including the ability to switch between technical and business contexts
- Participate in the Agile / Scrum process
