Bachelor’s or Master’s degree in computer science, machine learning, statistics, mathematics, or a related technical field
4+ years of hands-on experience in data science, machine learning, and statistical modeling
Proficiency in Python (pandas, NumPy, scikit-learn), deep learning frameworks (PyTorch, TensorFlow), and big data tools (Spark)
Deep understanding of data models, data pipelines, data transformations, feature engineering, and data quality management
Experience working with large-scale data from multiple systems, including APIs, databases, cloud storage, event streams, and third-party platforms
Expertise building GenAI applications including: Retrieval-Augmented Generation, Agentic workflows, Tool-using agents, Prompt orchestration, Evaluation frameworks, API-based model integrations
Strong understanding of MLOps, CI/CD, model monitoring, QA, risk management, and engineering best practices
Ability to translate ambiguous business problems into analytical, ML, and AI solutions
Collaborative mindset, humility, and strong ownership orientation
Willingness to travel domestically and internationally
Familiarity with marketing and customer data platforms such as Google Ads, Meta Ads, DV360, SA360, Campaign Manager, Adobe, Salesforce, CDPs, CRM systems, data clean rooms, or commerce platforms is preferred
Excellent communication and presentation skills, with the ability to explain complex technical concepts to both technical and non-technical stakeholders