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Organizational Analytics (OA) Data Scientist (NLP/LLM/GEN AI) - Consultant - Talent & Organization
Kuala Lumpur
Job No. r00116138
Full-time
Job Description
#LI-GM
YOUR ROLE
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
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
