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.
