Build and deploy models that serve predictions in milliseconds
Own the full ML lifecycle: feature engineering, training pipelines, model validation, A/B testing, monitoring for drift
Define research roadmap for predictive SEO intelligence and agent decision systems
Design experiments that prove business impact
Mentor data scientists and ML engineers

Requirements

7+ years applied data science experience
3+ years in production ML environments
Deep Python fluency - NumPy, Pandas, Scikit-learn, PyTorch or TensorFlow
SQL at scale - complex queries against terabyte datasets, query optimization
ML engineering mindset - feature stores, model serving, A/B testing, monitoring, drift detection
AI-native workflow - experience with AI coding tools
Scientific communication - clear explanation of complex methodologies
Research leadership - mentoring and coordination experience
Bonus: NLP/LLM expertise, Search or SEO domain knowledge, Reinforcement learning or bandit algorithms, Published research or active ML community presence

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonNumPyPandasScikit-learnPyTorchTensorFlowSQLfeature engineeringmodel validationA/B testing

Soft Skills

scientific communicationmentoringcoordinationresearch leadership