About Role:
Zycus is seeking a highly experienced AI / Machine Learning Architect with a strong background in Analytics, Data Mining, Machine Learning, NLP, Deep Learning, and Large-Scale Distributed Systems. The ideal candidate will act as a technical thought leader, creating and implementing AI solutions, mentoring teams, and driving strategic product development initiatives. Candidates with experience building AI products similar to IBM Watson (not just using it) are preferred.

Roles & Responsibilities:

Act as a technical thought leader in collaboration with analytics leadership.
Set strategy and standards for Machine Learning and advanced analytics.
Collaborate with senior leaders to explore opportunities for using advanced analytics across business functions.
Provide technical leadership, coaching, and mentoring to data scientists and analytics professionals.
Guide team members in applying advanced statistical, machine learning, and AI methodologies.
Review and ensure quality of work across Machine Learning projects.
Mentor junior team members on ML and data modeling applications.
Communicate and present insights effectively to stakeholders.
Apply advanced techniques including:
- Classification: SVM, Decision Tree, Random Forest, Neural Networks
- Regression: Linear, Polynomial, Logistic
- Classical Optimization: Gradient Descent, Newton-Raphson
- Graph Theory: Network Analytics
- Heuristic Optimization: Genetic Algorithms, Swarm Theory
- Deep Learning: LSTM, Convolutional Neural Networks, Recurrent Neural Networks

Must-Have Skills & Qualifications:

Total experience: 10+ years in AI, Machine Learning, and/or NLP.
Proven expertise in Artificial Intelligence (including deep learning algorithms) and Machine Learning.
Strong programming skills in Python or R.
Experience with large datasets and distributed computing (Hadoop ecosystem preferred).
Strong problem-solving skills and analytical mindset.
Fluency with databases and data management.

Preferred Qualifications:

Experience with advanced analytics, statistical modeling, and computational linguistics.
Familiarity with cloud computing, distributed systems, and big data technologies.
Knowledge of applied game theory, operations research, and information visualization.

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