Data Science Lead

Job Summary

The Data Science Supervisor leads ML solutions and guides our ML team of Data Scientits to new heights of technical prowess. In this role, you'll shape the strategic blueprint and spearhead the creation of robust, scalable ML solutions crafting innovative ML solutions ready for both showcase and deployment in real-world scenarios. By keeping abreast of the latest developments in the field, you will be pivotal in embedding best-in-class engineering practices within our team. This is a dynamic role at the forefront of technological innovation.

Essential Responsibilities

Machine Learning Strategy and Innovation
Technical Leadership and Architecture

Team Development and Mentorship

Operational Management and Best Practices

Communication and Collaboration

Minimum Qualifications

• Bachelors degree in a quantitative field such as Computer Science, Engineering, Physics, Statistics, or Applied Mathematics and 5 years in Data Architecture, Software engineering and Analytics.
  • 2 years leading data science and machine learning teams. • 1 years of healthcare experience. • 2 year of experience in AI/ML . • 2 year of regulatory experience in DeVSec Ops and CI/CD Pipeline. • Must stay on top of latest cutting edge technologies in and around AI/ML.

• Have a solid grasp of computer science fundamentals, software design, development lifecycle, and ML design patterns.
  • Understand core machine learning algorithms and principles. • Expert in Python and familiar with ML frameworks like Scikit-learn, TensorFlow, Keras, and PyTorch. • Extensive experience with cloud platforms and ML services such as Azure, including Azure ML, Databricks. • Experienced in deploying production-grade ML solutions both on-premises and in the cloud. • Proficient in implementing ML automation and MLOps with tools like MLflow and Kubeflow. • Knowledgeable in DevSecOps principles, employing CI/CD tools, and infrastructure as code practices with Github, Gitlab, Docker, and Kubernetes. • Familiar with Agile software development methodologies.