Sobre

Description We’re looking for a prediction engineer / quant researcher to help us design and implement scoring models and reinforcement learning methods for decision support in a marketing and e-commerce environment. Responsibilities Build predictive models and scoring functions from multi-source business data. Apply reinforcement learning / bandit techniques to guide optimization decisions. Translate noisy financial and marketing metrics into interpretable, actionable signals. Collaborate with engineering team to integrate models into a production workflow. Requirements Strong background in statistics, ML, or quantitative modeling. Hands-on experience with reinforcement learning / bandit frameworks. Skilled in Python (PyTorch/TF, scikit-learn, pandas). Ability to communicate modeling outputs clearly for operators and stakeholders. Bonus: experience with marketing, ad spend, or e-commerce data. Deliverables (first phase) Prototype scoring models using historical data. RL/bandit engine that can recommend scale/stop actions based on performance signals. Clear documentation of metrics, assumptions, and benchmarks. Engagement Contract role with potential extension. Remote, async-friendly.