Data Scientist - Anywhere in India/Multiple Locations - Awign

Awign Anywhere in India/Multiple Locations

5 days ago

permanent Technology / Internet

Description

About Awign Expert :

Awign Expert is an Enterprise focused platform that helps businesses Hire, Assess and Manage high skilled resources for Gig Based Projects.

We provide our Experts a gateway to work for and build a freelance/consulting career with large scale Enterprises. We are a newly launched business division of Awign, which is one of the pioneers and currently the largest player in the Gig Economy in India.

Here at Awign we are changing how the world works with a vision to uplift millions of Careers.

Job Title : LLM Finetuning

Experience : 4-5 years

Joining : Immediate

Location : Remote

Duration : 6 :

Evaluating and selecting the open source and/or commercial LLMs suitable for financial lending domains
Finetune the selected models for domain-specific tasks
Continuously monitor and measure model performance and improve model performance
Build and Manage model pipeline lifecycle - from getting datasets, cleaning datasets, finetuning the models, measuring model performance, deploying the models, monitoring and improving the model performance to meet business needs.

Essential Skills :

Python Programming: Proficiency in Python,
Working with libraries like TensorFlow, PyTorch, Transformers, NLTK, Pandas, sklearn, and other related libraries used in NLP tasks and finetuning language models.
Experience with building comprehensive Python modules for NLP tasks like tokenization, word embeddings, classifications, etc.
Proficiency in data preprocessing techniques such as text cleaning, tokenization, normalization, and handling of special characters is essential for preparing data for finetuning language models.
Knowledge of machine learning concepts like neural networks, optimization algorithms, and model evaluation techniques.
Deep learning expertise wrt NLP
Expertise on adapting pre-trained language models to specific tasks and domains
Experience with hyperparameter tuning methods such as grid search, random search, or Bayesian optimization for optimizing model performance during finetuning.
Experience in financial lending domain customer onboarding, loan servicing, and collections.
Expertise with tools and frameworks for handling large datasets.
Ability to evaluate model performance using appropriate metrics and interpret model predictions
Awareness of ethical considerations related to language models, such as bias mitigation, privacy preservation, and responsible AI practices
Ability to work with existing customer systems.

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