Data Scientist

Python Development:

• Leverage strong expertise in Python to develop robust, scalable solutions, utilizing advanced Object-Oriented Programming (OOP) principles.

AI/ML Implementation:

• Apply hands-on experience in machine learning concepts such as forecasting, clustering, regression, classification, and optimization using Python.

Cloud & Data Engineering Tools:

• Work with cloud-based tools and services including Azure, Databricks, MLflow, and orchestrate workflows using Airflow or similar tools.

MLOps & Automation:

• Implement MLOps best practices, including model deployment, monitoring, and lifecycle management. Utilize containerization tools like Docker for scalable deployments.

Version Control & Collaboration:

• Use Git for version control, supporting efficient collaboration and code management in team environments.

Problem-Solving & Communication:

• Demonstrate consistent problem-solving intent and initiative, with the ability to analyze complex technical challenges and deliver effective solutions.

Stakeholder Interaction:

• Communicate and present technical concepts clearly at various levels within the organization, both in verbal and written form.

Education and Work Experience:

• Bachelor's or Master's degree in Computer Science, Data Science, or a related field
• Proven experience in Python development with AI/ML and cloud-based implementations

Specialized Knowledge, Skills, and Abilities:

• Advanced Python and OOP concepts
• AI/ML algorithms and workflows
• Azure, Databricks, MLflow, Airflow
• MLOps, Docker
• Git and collaborative development
• Strong analytical and communication skills
• Ability to engage with both technical and non-technical stakeholders