Tech Stack

Description

You will lead high-impact data science initiatives end-to-end, from problem identification to deployment, driving measurable outcomes in revenue and efficiency. You'll architect advanced ML systems, set technical standards, and mentor team members while partnering with senior leadership to embed data-driven decision-making into core business strategy.

Requirements

• Bachelor's degree in Mathematics, Statistics, Computer Science; graduate degree preferred
• 7+ years of directly related data science experience (or 5+ with graduate degree)
• Expert-level proficiency in Python (pandas, NumPy, scikit-learn, TensorFlow, PyTorch, MLflow)
• Advanced mastery of statistical inference, experimental design, and machine learning
• Expert knowledge of SQL, distributed data processing (Spark, BigQuery, Snowflake), and cloud ML platforms (AWS, GCP, Azure)

Responsibilities

• Drive end-to-end ownership of high-complexity data science projects from problem definition to production deployment
• Architect and implement advanced ML systems (supervised, unsupervised, deep learning, ensemble methods, optimization)
• Define and champion best practices for model development, validation, deployment, and monitoring
• Translate ambiguous business challenges into well-scoped data science problems and deliver executive-level narratives
• Serve as technical lead and mentor for intermediate and junior data scientists