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.
