Data Science Engineer

• Develop and implement advanced AI/ML models to solve complex business problems and drive data-driven insights.
• Design, develop, and deploy machine learning algorithms and deep learning models using Python and popular frameworks like TensorFlow and PyTorch.
• Collaborate with cross-functional teams to understand data requirements and translate business problems into analytical solutions.
• Conduct data analysis and feature engineering to improve model accuracy and performance.
• Optimize and fine-tune models for better scalability and efficiency.
• Continuously research and stay updated on the latest trends and techniques in AI, machine learning, and deep learning.
• Work on large datasets, ensuring data integrity and quality while managing data preprocessing pipelines.
• Communicate findings through clear visualizations, reports, and presentations to both technical and non-technical stakeholders.

Required Skills & Knowledge:

• Strong proficiency in Python programming and libraries (e.g., NumPy, Pandas, Scikit-learn).
• Experience with deep learning frameworks like TensorFlow or PyTorch.
• Solid understanding of machine learning algorithms, data processing, and model evaluation techniques.
• Hands-on experience in data analysis, model deployment, and scaling AI systems.
• Strong analytical, problem-solving, and communication skills.

Preferred Qualifications:

• Degree in Computer Science, Data Science, Mathematics, or a related field.
• Experience with cloud-based AI/ML tools (e.g., AWS, Azure, Google Cloud).
• Familiarity with natural language processing (NLP) or computer vision is a plus.