Chief Decision Intelligence Engineer - Rio Branco - beBeeCustomerScience

Título do emprego: Senior Applied Scientist

Descrição

AI/ML Customer Science Specialist

We are seeking an AI/ML Customer Science specialist to develop and deploy advanced machine learning systems that drive business growth.

In this role, you will design, build, and maintain scalable ML solutions across acquisition, conversion, retention, and revenue optimization.

About the Role:

You will work at the intersection of machine learning experimentation causal inference strategy in a fast-paced collaborative entrepreneurial environment. You will build models platforms creating impact areas sales prioritization expected value modeling marketing targeting uplift modeling attribution incrementality measurement customer lifecycle modeling conversion retention churn LTV outreach optimization personalization systems responsibilities research design develop machine learning statistical causal models Marketing Sales use cases propensity expected value modeling uplift treatment effect estimation attribution forecasting prioritization systems translate business problems clear objectives loss functions evaluation frameworks design feature representations capturing customer behavior engagement dynamics analyze experiments A/B geo diff-in-diff causal impact own end-to-end ML lifecycle data ingestion training deployment monitoring develop scalable services integrated business workflows CRM marketing internal tools partner close with Product Engineering Marketing Data teams influence technical direction roadmap based on business impact communicate insights model behavior technical non-technical stakeholders mentor junior scientists engineers help establish best practices contribute long-term data science strategy platforms innovation minimum qualifications 5+ years industry experience applied Machine Learning Master's degree PhD Computer Science Machine Learning Statistics Operations Research related field experience building deploying managing ML models production scale strong knowledge ML best practices feature engineering experimentation pipelines model evaluation modern techniques including gradient boosting deep learning transformers optimization computer vision casual inference experience plus proficiency Python SQL hands-on experience ML frameworks PyTorch TensorFlow Keras Scikit-learn strong data skills large-scale datasets big tools Apache Beam Kafka Spark cloud AWS GCP Azure preferred qualifications PhD CS related field applying retail commercial contexts familiarity MLOps production pipelines leadership mentoring impact-driven mindset focus delivering high-quality scalable solutions