Responsibilities

• Deliver advanced analytics solutions in the area of deep learning and machine learning.
• Apply Deep Learning, Time Series Analysis, NLP, XGBoost, Autoencoder, Keras and Tensorflow to provide predictive analytics solutions and extract actionable insights.
• Develop Deep Learning models to solve business problems.
• Leverage and/or develop innovative data mining and machine learning methods to solve novel and diverse business problems.
• Quantify the effectiveness and value of innovations with subject matter experts.
• Lead projects independently until results meet the internal stakeholder requirements.
• Be the subject matter expert and mentor other data scientist.
• Ability to teach in our analytics upskilling program and coach participants when required.
• Understand business requirement to build reliable data infrastructure using big data technologies.
• Build AI/ML models. Apply ML algorithms and libraries. Train and retrain ML systems and models. Tune and analyze AI/ML algorithms and extract actionable insights.
• Play a key role in MLOps : Follow machine learning model management, lifecycle best practices, and MLOps for all AI/ML models created. Understanding of the complete analytics lifecycle and applications.
• Design ML systems. Research and implement ML algorithms and tools.

Requirements

• More than 10 years of experience in Python (and basic ML libraries), and SQL.
• Proficient in git version control. Experience working in an agile environment.
• Solid technical knowledge and hands-on skills in machine learning engineering, deep learning, statistical algorithms, data mining, and data structures.
• Hands-on experience in solving analytics problems related to complex time-series data and/or text data.
• Experience in working with HDD cert log and cert data.
• Thesis or research experience in topics related to natural language processing, artificial intelligence, and machine learning would be a plus.
• Proven record of accomplishment in delivering analytics solutions using TensorRT, Keras, Tensorflow, PyTorch, and CNN.
• Understanding of containerization, CI/CD, RESTful web services, web applications, and dashboard development.