Job Description :
Required Skills:
5+ years’ experience with Masters or PhD in the following areas:
Natural Language Processing and Machine Learning (familiarity with deep learning and neural networks a plus)
Software engineering skills in one or more object-oriented languages (C++/Java) and scripting language (Python/R)
Implementing Machine Learning and Natural Language Processing algorithms/software
Training, customizing and establishing AI software utilizing Machine Learning and Natural Language Processing algorithms
Customizing and extending software using different packages and APIs
Rapid prototyping for creating/evaluating different experimental use cases

Education/Certifications: Masters or PhD in Computer Science or related discipline

This practice is seeking a Knowledge Engineer with deep understanding and practical experience in a few areas of AI and Big Data analytics:
Natural-Language Processing and Text Analytics
Machine Learning
Reasoning Engines, Ontology Creation and Predictive Modeling The position reports into the Vice President responsible for this practice.

Job Description:
Demonstrate expertise in advanced computing practices such as: o Natural Language Processing with Textual Analytics o Machine Learning o Sentiment analysis & identification o Cognitive computing o Multi-strategy Reasoning and Learning
Work closely with different business units to implement and extend Natural Language Processing and Machine Learning software for particular use cases within the Bank
Carry out Proof of Concepts and rapid prototyping
Support transitions to project implementation – be engaged and support the TSG team responsible for building the production ready solution
Vendor selection – work with the Vendor Management Office to select the appropriate set of technology vendors for the Proof of Concepts
Findings and recommendations – participate in documenting and presenting the results as well as provide recommendations for next steps The candidate will maintain/develop expertise in the following areas:
Semantics and Interoperability over (unstructured and structured) Big Data and applications
Knowledge Representation in ontology languages such as OWL, RDF
Ontology engineering and design using ontology editors such as Protégé or TopBraid
Distributed Algorithms for processing Big Data
Dynamic Programming for evolving existing complex rule systems to be adaptable

General Skills:
Problem Solving
Solution Architecting
Business Analysis
Written and verbal communications
Strong initiative, ability to self-manage and also work in a team environment