Data Scientist

About the Company

Celebal Technologies is a leading software service provider specializing in Data Science, Big Data, and Enterprise Cloud solutions. The company leverages advanced technologies like Robotics, Artificial Intelligence, and Machine Learning algorithms to deliver innovative data-driven solutions that enhance business efficiency in an interconnected digital world.

Job Overview

We are looking for a talented and innovative Data Scientist to join our vibrant team. The ideal candidate will have expertise in Classical Machine Learning, Conversational AI, and Deep Learning systems, with a keen ability to transform complex mathematical problems into practical machine learning models. The role involves building AI-powered systems that provide seamless and interactive experiences, alongside engaging in a diverse range of Natural Language Processing (NLP) projects, including optimizing prompts to improve the functionality of Large Language Models.

Key Responsibilities

• Develop cutting-edge Generative AI models including GANs, VAEs, and Transformer architectures.
• Create and implement classical machine learning models such as regression, decision trees, SVMs, random forests, gradient boosting, clustering, and dimensionality reduction to tackle challenging business problems.
• Train, fine-tune, and deploy deep learning models including CNNs, RNNs, LSTMs, GANs, and Transformers to address AI challenges and enhance system performance.
• Engage in NLP projects by refining and optimizing prompts to boost the effectiveness of Large Language Models like GPT, BERT, and T5.
• Manage extensive datasets through preprocessing, augmentation, and feature engineering to prepare data for machine learning and deep learning pipelines.
• Optimize model parameters using techniques such as grid search, random search, and Bayesian optimization to improve key performance indicators including accuracy, precision, recall, and F1 score. Monitor models to mitigate issues like drift, overfitting, and bias.
• Conduct thorough code and design reviews to maintain system scalability and quality. Collaborate with engineering teams to assess algorithm performance and validate models.
• Work closely with cross-functional teams comprising data scientists, engineers, and product managers to integrate machine learning solutions into production environments. Keep abreast of emerging AI/ML trends and incorporate innovative methods into ongoing projects.

Candidate Qualifications

• Possesses a Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, Data Science, or a closely related discipline.
• Demonstrates extensive experience with classical machine learning algorithms (such as regression, SVMs, decision trees) and deep learning frameworks (neural networks, transformers). Skilled in TensorFlow, PyTorch, or Keras.
• Experienced in NLP with significant work on Large Language Models like GPT, BERT, or T5. Knowledge of prompt engineering and model fine-tuning is highly valued.
• Proficient in Python and libraries including NumPy, Pandas, Scikit-learn, and NLP tools like Hugging Face Transformers, NLTK, and SpaCy.
• Strong background in statistical modeling, probabilistic theory, and mathematical optimization relevant to machine learning applications.
• Practical experience deploying machine learning models on cloud platforms such as AWS SageMaker, Azure ML, or Google Cloud AI, alongside knowledge of MLOps best practices.
• Skilled in code review, system design, and ensuring scalability and maintainability of AI/ML systems. Knowledge of distributed computing and parallel processing is an advantage.

Behavioral and Soft Skills

• Proactive team player with a high level of self-motivation and commitment to achieving successful outcomes.
• Excellent verbal and written communication abilities in English.
• Strong presentation skills combined with meticulous attention to detail.
• Eager to continuously learn and apply new techniques and technologies.
• Accountable and responsible for assigned duties.
• Demonstrates reliability, integrity, and trustworthiness consistently.
• Effective time management capabilities, able to handle urgency and meet or exceed deadlines.
• Capable of processing large volumes of work accurately within set timelines.