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Data Scientist

2 months ago

delhi, India ADP Full time
Role Overview:
We are seeking a highly skilled NLP Data Scientist with a strong background in Text Mining, Natural Language Processing, Data Science, Big Data, and advanced algorithms. The ideal candidate will have full-cycle experience in large-scale Text Mining/NLP projects, ranging from defining a business use case to executing solutions and managing change.
Experience 3-8 Years
Key Responsibilities:
Lead and execute end-to-end NLP/Text Mining projects, Text Analytics assessment.
Develop and implement AI/ML methodologies, including Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), and Neural Networks for Information Retrieval and Extraction.
Apply advanced NLP techniques such as Dependency Parsing, Chunking, and Summarization.
Build and maintain ontology -based solutions and develop chatbots (if experienced).
Should be able to parse and preprocess PDFs , images for creating knowledge base.
Required Skills and Experience:
Natural Language Processing (NLP) & AI: Expertise in NLP techniques, including Sentiment Analysis, Contextual NLP, Parsing, Dependency Parsing, Summarization, etc.
Machine Learning/Deep Learning: Solid understanding of ML/DL models and algorithms, including Neural Networks and Information Retrieval.
Text Analytics: Experience in large-scale text analytics projects and full-cycle implementation.
Programming: Proficient in Python with strong hands-on experience with libraries like pandas, numpy, scikit-learn, tensorflow, and/or pytorch.
Data Structures: Proficient in working with data structures and algorithms relevant to machine learning and data analysis.
MLops & Cloud Computing:
Strong experience with MLOps, preferably on cloud platforms like AWS.
Hands-on experience with tools like Amazon SageMaker or Databricks for model training and batch inference.
Knowledgeable in building and managing machine learning pipelines for efficient model deployment.
Proficient in cloud services and containerization (Docker, Kubernetes).
Understanding of key ML evaluation metrics (precision, recall, F1-score) and experience in model monitoring and drift detection.
Data Analysis & Statistical Skills:
Expertise in performing Exploratory Data Analysis (EDA) and data preparation for machine learning models.
Strong knowledge of hypothesis testing algorithms (Chi-square, Z-test, t-test) and anomaly/outlier detection.
Capable of performing statistical computations such as mean, median, percentiles, standard deviation, and interquartile range.
Proficient in creating training and validation datasets for model evaluation.
Preferred Qualifications:
Experience in developing and deploying chatbots is a plus.
Familiarity with ontology and semantic technology applications.
Proficient in AWS services and MLOps tools like SageMaker, Databricks, or other cloud-based platforms.
Strong understanding of the machine learning lifecycle, from experimentation to production deployment.
Able to build APIs for ML models and ensure they are scalable, reliable, and maintainable.
Additional Skills:
Strong problem-solving abilities and analytical thinking.
Effective communication skills to collaborate with technical and non-technical stakeholders.
Ability to translate business needs into technical solutions and deliver impactful results.
Education and Experience:
Master’s degree in Data Science, Machine Learning, Statistics, or a related field.
Relevant years of experience in NLP, Machine Learning, and Big Data analytics.