core data scientist

Role Overview

We are looking for an experienced Core Data Scientist with 5+ years of hands-on experience in Machine Learning, Natural Language Processing (NLP), and Deep Learning. The ideal candidate should have strong expertise in developing, deploying, and optimizing data science models to solve complex business problems.

Key Responsibilities

• Develop and implement advanced Machine Learning, NLP, and Deep Learning models.
• Work on end-to-end data science projects, including data preparation, feature engineering, model development, validation, and deployment.
• Apply statistical and machine learning techniques to identify patterns, trends, and actionable insights.
• Build NLP solutions for tasks such as text classification, sentiment analysis, entity extraction, text similarity, and language understanding.
• Develop and optimize deep learning architectures using relevant frameworks.
• Experiment with different algorithms and approaches to improve model accuracy, scalability, and performance.
• Collaborate with engineering, product, and business teams to translate business requirements into data science solutions.
• Perform model evaluation, tuning, experimentation, and continuous improvement.
• Stay updated with emerging developments in AI, Machine Learning, NLP, and Deep Learning.

Required Skills

• 5+ years of relevant experience in Data Science / Machine Learning.
• Strong hands-on expertise in Machine Learning and Deep Learning.
• Strong experience in NLP / Natural Language Processing.
• Proficiency in Python and commonly used data science libraries.
• Strong understanding of supervised and unsupervised learning algorithms.
• Experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras.
• Strong knowledge of feature engineering, model evaluation, hyperparameter tuning, and statistical techniques.
• Good understanding of NLP techniques, text processing, embeddings, transformers, and language models.
• Strong analytical, problem-solving, and communication skills.

Good to Have

• Experience with Generative AI, LLMs, Transformers, RAG, or Vector Databases.
• Exposure to cloud platforms such as AWS, Azure, or GCP.
• Experience deploying ML models into production environments.
• Knowledge of MLOps and model lifecycle management.