Principal Data Scientist

Principal Data Scientist

• Lead end-to-end data science projects from problem formulation through model development, deployment, and monitoring in production environments.
• Design and implement advanced machine learning algorithms, statistical models, and AI solutions that drive business value.
• Provide technical leadership and mentorship to junior data scientists and data engineers, fostering a culture of excellence and continuous learning.
• Partner with engineering teams to architect scalable data pipelines and ML infrastructure.
• Establish best practices for experimentation, model training, model evaluation, and monitoring.
• Stay current with the latest advancements in data science, machine learning, and artificial intelligence.
• Collaborate with cross-functional teams, including product, engineering, and business stakeholders, to identify and address key business challenges.
• Present findings and recommendations to senior leadership and other stakeholders.

• Masters or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field.
• 10+ years of experience in data science or a related field (at least the last 5 years in data science), with a proven track record of leading impactful projects that achieve clear customer outcomes through product delivery .
• Deep expertise in machine learning techniques, including supervised and unsupervised learning, deep learning, NLP, computer vision, or reinforcement learning
• Strong programming skills in Python or R, with experience in ML frameworks (TensorFlow, PyTorch, scikit-learn)
• Proficiency in SQL and experience working with large-scale datasets and distributed computing frameworks (Spark, Dask)
• Demonstrated experience deploying models to production and monitoring model performance
• Demonstrated cross-functional experience with diverse teams across the organization
• Excellent communication skills with the ability to explain complex technical concepts to non-technical audiences
• Strong business acumen and ability to connect data science work to organizational objectives
• Experience mentoring and developing junior team members

• Experience in cloud platforms (AWS, GCP, Azure) and MLOps practices
• Track record of publishing research or contributing to open-source projects
• Experience with A/B testing and causal inference methodologies
• Knowledge of data engineering principles and ETL processes
• Leadership experience in managing or leading data science teams