Description

You will develop and deploy machine learning models for predictive analytics, classification, and optimization. You own the full lifecycle from data cleaning and feature engineering to model evaluation and cloud deployment on AWS, Azure, or GCP.

Responsibilities

• Develop and implement ML models for predictive analytics and optimization.
• Clean, preprocess, and engineer features from large datasets.
• Deploy scalable ML models on cloud platforms (AWS, Azure, GCP).
• Evaluate, tune, and validate models for accuracy and performance.
• Present data-driven insights and recommendations to stakeholders.

Required Skills

• 5+ years of experience in Data Science or related field.
• Strong proficiency in Python, including NumPy, Pandas, and Scikit-learn.
• Hands-on experience with AI/ML algorithms and statistical modeling.
• Expertise in deploying models on AWS, Azure, or GCP.
• Solid understanding of data structures, algorithms, and distributed computing.
• Experience with SQL/NoSQL databases and data pipelines.
• Bachelor's or Master's degree in Computer Science, Data Science, or related field.

Preferred Skills

• Experience with MLOps frameworks (Kubeflow, MLflow, Airflow).
• Knowledge of big data tools like Spark and Hadoop.

Key Skills

Education

Bachelor's or Master's degrees