
Data Scientist (AI & Advanced Analytics)
- USA
- Permanent
- Full-time
- Innovative Data Solutions o 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.
- Model Development & Productization o 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.
- Cross-Functional Collaboration o Support the development of intelligent tools and platforms that can be scaled across multiple use cases.
- Engage in product thinking (through workshops and other forums) to ensure data solutions are user-friendly, modular, and aligned with business needs.
- Insight Generation & Storytelling (in collaboration with BUs) o Collaborate with business units to turn insights into actionable, productized outputs.
- Support BUs in conducting deep-dive analyses to uncover meaningful insights from structured and unstructured data.
- Visualize and communicate findings in a clear, business-relevant narrative that informs decision-making.
- Responsible AI & Governance o Ensure all data solutions are developed with privacy and compliance requirements in mind.
- Document data model and product assumptions, methodologies, and limitations to support responsible use and ongoing maintenance.
- Bachelor's or Master’s degree in Data Science, Computer Science, Engineering, or a related field.
- 3-10 years of experience in data science, analytics, or applied machine learning.
- 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.
- 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.