Red Nucleus is looking to transform how they work, make decisions, and deliver services by building and productizing innovative data solutions, specifically AI-driven products and insights that are scalable, sustainable, and operationally embedded across the enterprise for both internal use and client delivery.
Requirements
- Strong programming skills in various languages (for example: python, R, etc, with broad experience in libraries (for example: such as scikit-learn, TensorFlow, or PyTorch).
- Proficient in working with cloud-based data platforms (for example: Snowflake, AWS, Azure, Databricks).
- Hands-on experience operationalizing models or data pipelines in production environments.
- Solid understanding of statistics, machine learning, and model performance evaluation.
- Experience developing or contributing to data products or AI-powered tools preferred.
Responsibilities
- Identify high-impact opportunities for AI and advanced analytics to create new product capabilities.
- Contribute to the design and evolution of data products, from early prototype to full-scale deployment (build in collaboration with a broader team, either internal or external)
- Help develop frameworks for data solution productization, ensuring repeatability, governance, and ease of adoption.
- Design and build machine learning models and algorithms that solve core business challenges.
- Translate models into production-ready, reusable components that can be deployed at scale across business units for both internal and client use.
- Collaborate with BUs and other data scientists / engineers (internal or outsourced) to package, deploy, and maintain data products and services that drive efficiency and innovation.
- Support the development of intelligent tools and platforms that can be scaled across multiple use cases.
Other
- A builder’s mindset, excited to move from model to product and drive measurable business impact.
- Curiosity, creativity, and a passion for innovation.
- Strong communication skills and a desire to work collaboratively across technical and nontechnical teams.
- A commitment to quality, ethics, and continuous improvement in everything you deliver.
- Bachelor's or Master’s degree in Data Science, Computer Science, Engineering, or a related field.
