Associate Director- NLP / ML

Talent Worx is a growing services & recruitment consulting firm, we are hiring for our client which is a globally leading provider of financial intelligence, data analytics, and AIdriven solutions, empowering businesses worldwide with insights for confident decision-making. Join to work on cuttingedge technologies, drive digital transformation, and shape the future of global markets.

Requirements

What's in for you

• Designing and developing NLP applications
• Using effective text representation techniques and classification/similarity algorithms
• Training, evaluating and deploying models
  

Job briefWe are looking for a Natural Language Processing Engineer to help us improve our NLP products and create new NLP applications.NLP Engineer responsibilities include transforming natural language data into useful features using NLP techniques to feed classification algorithms. To succeed in this role, you should possess outstanding skills in statistical analysis, machine learning methods and text representation techniques.Your ultimate goal is to develop efficient self-learning NLP applications.

Responsibilities

• Study and transform data science prototypes
• Design NLP applications
• Select appropriate annotated datasets for Supervised Learning methods
• Use effective text representations to transform natural language into useful features
• Find and implement the right algorithms and tools for NLP tasks
• Develop NLP systems according to requirements
• Train the developed model and run evaluation experiments
• Integrate the models in application flow and deploy at scale
• Perform statistical analysis of results and refine models
• Extend ML libraries and frameworks to apply in NLP tasks
• Remain updated in the rapidly changing field of machine learning
  

Requirements And Skills

• Proven experience as an NLP Engineer or similar role
• Understanding of NLP techniques for text representation, semantic extraction techniques, data structures and modeling
• Ability to effectively design software architecture
• Deep understanding of text representation techniques (such as n-grams, bag of words, sentiment analysis etc), statistics and classification algorithms
• Knowledge of Python and Java
• Ability to write robust and testable code