Data Scientist

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.