Primary : Python, SQL, Gen AI, NLP, ML, and Deep Learning techniques
Secondary: Data Analysis and Processing, Data Visualization
Exploratory Data Analysis (EDA): Conduct thorough exploratory data analysis to uncover insights and trends from raw datasets.
SQL: Proficiency in SQL to extract, manipulate, and analyze large datasets from relational databases.
AI/ML Models: Strong experience in designing, building, and deploying AI or Gen AI based solutions.
Cloud Technology : Must have a strong exposure in deploying AI/ Gen AI Models in Cloud
Machine Learning: In-depth understanding and practical experience with machine learning algorithms and techniques.
Deep Learning: Hands-on experience in deep learning models, particularly in NLP and computer vision.
Natural Language Understanding (NLU): Expertise in applying NLU techniques to process and understand human language data.
Python: Strong programming skills in Python, especially for data science tasks and NLP.
Hugging Face Transformers: Experience with Hugging Face Transformers library for implementing state-of-the-art NLP models.
BERT: Expertise in utilizing BERT for a variety of NLP tasks including text classification, named entity recognition, and question answering.
NLP Algorithms: Knowledge of advanced NLP algorithms and techniques for text analysis and understanding.
Model Fine-Tuning: Ability to fine-tune pre-trained models to improve their performance on domain-specific tasks.
Text Analytics: Experience in text mining and extracting useful insights from large text datasets.
Machine Learning Frameworks: Proficiency with machine learning frameworks like TensorFlow and PyTorch.
Data Analysis and Processing: Strong skills in data analysis and preprocessing and feature engineering for model readiness.
Data Visualization: Ability to present complex data and insights using visualization tools like Matplotlib, Seaborn, or similar.
State-of-the-Art NLP Models: Integrate and apply cutting-edge NLP models and algorithms to extract valuable insights from large text datasets.
Cross-functional Collaboration: Work closely with cross-functional teams to understand business needs and translate them into technical solutions using NLP techniques.
Reporting and Presentation: Present findings and insights to stakeholders through clear, concise, and compelling reports and presentations.
Qualifications:
Minimum 5+ years of experience in Data Science, particularly with Gen AI, NLP, ML, and Deep Learning techniques.
Strong analytical and problem-solving skills.
Ability to communicate complex technical concepts to non-technical stakeholders.
Excellent teamwork and collaboration skills in a dynamic environment.
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