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Organizational Analytics (OA) Data Scientist (NLP/LLM/GEN AI) - Management Consultant (Talent & Organization)
Kuala Lumpur
Job No. r00285314
Full-time
Job Description
Job Responsibilities:
Although no two days at Accenture are the same, as an Organizational Analytics (OA) Scientist (NLP) in our Talent & Organization (T&O) practice, a typical day might include:
Fetching information from various sources and analyzing it to better understand people behaviors
Use of Natural Language Processing (NLP) Algorithm- Static and Dynamic Word Embeddings, Transfer Learning using Deep Learning Framework
Working knowledge on development, deployment and prototyping Gen AI / LLM solutions to improve the product landscape
Working with cloud platforms and services for GenAI development, such as Azure for using OpenAI models.
Train NLP Models for prescribed requirements: Supervised and Unsupervised topic modeling
Web Scraping for data mining using state-of-the-art methods
Run numeric simulations leveraging different statistic techniques
Selecting features, building and optimizing classifiers using machine learning techniques
Processing, cleansing, and verifying the integrity of data used for analysis
Doing ad-hoc analysis and presenting results in a clear manner
Doing custom analytics to deliver insights to clients
Contribute to authoring of Thought leadership and research papers
Contribute to innovation and new product development in the people and organization analytics space
Qualifications
Key Qualifications:
Bachelor/Master’s degree in Statistics, Mathematics, Computer Science, Engineer, or Social Sciences
3 to 5 years of experience in Natural Language Processing (NLP), Machine Learning and research
1 year GenAI model/application development experience using methodologies like Retrieval Augmented Generation(RAG), Few shot learning etc.
LLM Engineering skills for enabling teams to quickly and efficiently deploy GenAI applications within cloud environment like Azure, AWS etc.
Data fluency and working knowledge of statistical methodologies
Data interpretation with working knowledge of analytic models and digital tools (coding experience desirable)
Fluency in English
Ability to perform in a non-structured and dynamic environment
Desirable: Code (e.g., Python, R ) developer experience, including writing and testing code, debugging programs
and deploying the models or integrating applications with third-party web services
