Ph.D. in Computer Science, Data Science, or related field.
A strong background in text mining and natural language processing, with experience in different NLP tasks, transfer learning and models like RNN, BERT, GPT etc.
A strong background in scientific computing, complemented by understanding of computer architecture, as well as distributed and parallel computing.
Demonstrated work experience with extract, transform, and load (ETL) for large-scale, complex data sets.
Experience with data analytics and database design
Demonstrated knowledge of system engineering, object-oriented design, information risk and security guidelines.
Knowledge of version control systems as software configuration management and source code lifecycle management tools.
Experience in data architecture and application architecture, target state design and strategy.
Experience with system integration.
Experience in developing and deploying AI solutions, with a focus on text analytics and natural language processing.
Understanding of cloud technologies and services.
Experience with unstructured data and NoSQL Databases, such as MongoDB.
Ability to use different scripting languages, understanding the nuances and benefits of each.
Ability to research and discover new methods to acquire data, and new applications for existing data.
Ability to apply knowledge, skills, tools, or techniques to complex programs and project activities to meet the specific business and technical program (including security) or project requirements.
Ability to research, design, develop, implement, and manage applications based on specific business needs.
Proficiency in programming languages, including Python, R, SQL, Python, C/C++, Ruby, Perl, Java, and MatLab.
Responsibilities:
Collaborates with users to deliver big data, AI and machine learning models and solutions.
Designs and implements efficient, adaptable, scalable, and reliable pipelines and algorithms to process unstructured and structured data.
Develops and deploys AI/ML solutions that utilize natural language processing techniques.
Develops and maintains custom data pipelines and workflows for large-scale text analytics projects.
Implements new statistical or other mathematical methodologies as needed for specific models or analysis.
Researches and analyzes complex data sets, combining different sources and types of data to develop machine learning based models making value out of data.
Uses AI/ML to empower business with novel capabilities such as automating processes by utilizing machine learning.
Prototypes solutions and conducts experiments highlighting results and lessons learned.
Provide technical expertise and guidance to users on AI/ML and machine learning best practices.
Helps the users evaluate the AI solution from a technical perspective.
Leverages industry knowledge and stays close to latest technology trends.
Contributes to the development of sample applications, tutorials, presentations and training material for big data and machine learning technologi