The company, a VC-backed AI product intelligence platform, is looking to solve the problem of de-risking product bets and personalizing experiences before launch by building a simulation engine for adaptive software.
Requirements
- Strong proficiency in Python for data science and machine learning workflows, with hands-on experience in frameworks like PyTorch, TensorFlow, or Scikit-learn.
- Expertise in large-scale unstructured data manipulation, specifically inferring user characteristics and traits from complex datasets.
- Solid experience preparing comprehensive reports and slide decks for user segmentation and behavioral insights, coupled with a strong foundation in statistics, probability, and causal inference.
Responsibilities
- Build and optimize robust data pipelines (ETL/ELT) across SQL/NoSQL systems, ensuring reliability and quality of large-scale event/log data.
- Collaborate with GenAI experts, behavioral scientists, and ML engineers to create synthetic personas and customer-ready reports and presentations.
- Apply advanced statistical modeling, causal inference, and machine learning to analyze user behavior, design experiments, and generate actionable insights.
Other
- Degree requirements not specified, but strong educational foundation implied.
- Travel requirements not specified.
- Visa requirements not specified.
- Strong foundation in statistics, probability, and causal inference required.
- Ability to communicate complex technical concepts to non-technical stakeholders implied.
