Responsibilities
- Collaborate with product and customer support teams to translate vague customer requirements into defined data science or engineering challenges
- Test and assess various approaches to build robust, high-performing prototypes
- Partner with engineers to convert experimental models into scalable, production-ready systems
- Develop and assess agentic systems by designing proof-of-concept models, integrating tools, and measuring performance
- Lead initiatives that combine statistical analysis, business strategy, communication, and software engineering
- Help shape both immediate and long-term product development plans
- Apply diverse data science methods such as machine learning, deep learning, network analysis, multilingual text analysis, sampling techniques, and data visualization to generate actionable insights
- Plan and carry out experiments to test the reliability of data collection and sampling approaches
- Perform on-demand analyses and create prototype tools to assist subject matter experts and support staff
- Engage in high-level conversations about the future direction of data science within the organization
Work Arrangement
Hybrid
