Remote Principal Data Scientist

Description:

• Tiger Analytics is seeking an experienced Principal Data Scientist to join their advanced analytics consulting firm.
• The firm specializes in Machine Learning, Data Science, and AI, serving multiple Fortune 500 companies.
• The role requires a highly experienced Machine Learning Architect with over 10 years of experience in data science, machine learning, and MLOps.
• Responsibilities include designing and delivering end-to-end ML solutions across diverse business domains.
• The position involves collaboration with data scientists, engineers, product teams, and business stakeholders to architect robust and scalable solutions.
• The candidate will drive strategy by leveraging analytical skills to ensure business value and communicate results.
• Key tasks include designing system architecture for ML and AI solutions, leading ML system design discussions, and architecting cloud-native platforms for ML model training and deployment.
• The role also involves building reusable components, enforcing best practices in model versioning and CI/CD, and managing machine learning and data pipelines in production.
• Participation in fast iteration cycles and collaboration within a cross-functional Agile team is essential.
• The candidate must possess excellent communication and teamwork skills and be able to work with a global team.

Requirements:

• A Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field is required.
• The candidate should have 10+ years of hands-on experience developing advanced analytics solutions in a corporate environment, with at least 4 years of programming experience in Python.
• A minimum of 7 years of experience in productionizing, monitoring, and maintaining models is necessary.
• Strong programming skills in Python and familiarity with ML libraries such as scikit-learn, TensorFlow, and PyTorch are essential.
• Deep experience with MLOps tools like MLflow, Kubeflow, Airflow, SageMaker, or Vertex AI is required.
• Hands-on experience designing ML systems using cloud platforms such as AWS, Azure, or GCP is necessary.
• A strong understanding of data engineering, APIs, CI/CD pipelines, and model observability is required.
• Excellent communication and stakeholder management skills are essential for this role.

Benefits:

• This position offers significant career development opportunities in a fast-growing and challenging entrepreneurial environment.
• The role provides a high degree of individual responsibility, allowing for personal and professional growth.
• Employees will have the chance to work with top-notch talent and contribute to building a leading global analytics consulting team.