Data Scientist

Celebal Technologies; Jaipur; On-site; INR 1,500,000 - 2,800,000; Full time

Job summary

Celebal Technologies in Jaipur, Rajasthan, seeks a skilled Data Scientist to advance ML and NLP systems and translate complex math into actionable models. The role focuses on Generative AI, classical ML, and deep learning, with emphasis on refining prompts for large language models.

You will handle data preprocessing, feature engineering, model evaluation, and deployment, collaborating with cross‑functional teams to deliver scalable AI solutions.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, Data Science, or related field.
• Experience with ML techniques (classical and deep learning) and frameworks (TensorFlow, PyTorch, Keras).
• NLP expertise with LLMs (GPT, BERT, T5) and prompt engineering
• Proficient Python and libraries (NumPy, Pandas, Scikit-learn, Hugging Face).
• Knowledge of deploying ML models using cloud platforms (SageMaker, Azure ML, GCP).
• Strong statistical and mathematical optimization knowledge.

Responsibilities

• Generative AI solutions: build and fine-tune GANs, VAEs, Transformers.
• Classical ML: develop models for regression, trees, SVMs, clustering, dimensionality reduction.
• Deep Learning: train, fine-tune, and deploy CNNs, RNNs, LSTMs, GANs, Transformers.
• NLP/LLM optimization: refine prompts to improve GPT/BERT/T5 outputs.
• Data management & feature engineering on large datasets.
• Model evaluation, hyperparameter tuning, drift and bias monitoring.
• Code review and design for scalable AI/ML systems.
• Collaborate with cross-functional teams to productionize ML solutions.

Skills

Python

NumPy

Pandas

Scikit-learn

TensorFlow

PyTorch

Keras

Hugging Face Transformers

NLTK

SpaCy

GPT

BERT

T5

Education

Bachelor’s or Master’s degree in CS, Mathematics, Statistics, Data Science

Tools

AWS SageMaker

Azure ML

GCP AI

Job description

We are seeking a highly skilled and innovative Data Scientist to join our dynamic and forward-thinking team. This role is ideal for someone who is passionate about advancing the fields of Classical Machine Learning, Conversational AI, and Deep Learning Systems, and thrives on translating complex mathematical challenges into actionable machine learning models. The successful candidate will focus on developing, designing, and maintaining cutting-edge AI-based systems, ensuring seamless and engaging user experiences. Additionally, the role involves active participation in a wide variety of Natural Language Processing (NLP) tasks, including refining and optimizing prompts to enhance the performance of Large Language Models (LLMs).

Key Responsibilities:

• Generative AI Solutions: Develop innovative Generative AI solutions using machine learning and AI technologies, including building and fine-tuning models such as GANs, VAEs, and Transformers.
• Classical ML Models: Design and develop machine learning models (regression, decision trees, SVMs, random forests, gradient boosting, clustering, dimensionality reduction) to address complex business challenges.
• Deep Learning Systems: Train, fine-tune, and deploy deep learning models such as CNNs, RNNs, LSTMs, GANs, and Transformers to solve AI problems and optimize performance.
• NLP and LLM Optimization: Participate in Natural Language Processing activities, refining and optimizing prompts to improve outcomes for Large Language Models (LLMs), such as GPT, BERT, and T5.
• Data Management & Feature Engineering: Work with large datasets, perform data preprocessing, augmentation, and feature engineering to prepare data for machine learning and deep learning models.
• Model Evaluation & Monitoring: Fine-tune models through hyperparameter optimization (grid search, random search, Bayesian optimization) to improve performance metrics (accuracy, precision, recall, F1-score). Monitor model performance to address drift, overfitting, and bias.
• Code Review & Design Optimization: Participate in code and design reviews, ensuring quality and scalability in system architecture and development. Work closely with other engineers to review algorithms, validate models, and improve overall system efficiency.
• Collaboration & Research: Collaborate with cross-functional teams including data scientists, engineers, and product managers to integrate machine learning solutions into production. Stay up to date with the latest AI/ML trends and research, applying cutting-edge techniques to projects.

Qualifications:

• Educational Background: Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, Data Science, or any related field.
• Experience in Machine Learning: Extensive experience in both classical machine learning techniques(e.g., regression, SVM, decision trees) and deep learning systems (e.g., neural networks, transformers).Experience with frameworks such as TensorFlow, PyTorch, or Keras.
• Natural Language Processing Expertise: Proven experience in NLP, especially with Large Language Models (LLMs) like GPT, BERT, or T5. Experience in prompt engineering, fine-tuning, and optimizing model outcomes is a strong plus.
• Programming Skills: Proficiency in Python and relevant libraries such as NumPy, Pandas, Scikit-learn, and natural language processing libraries (e.g., Hugging Face Transformers, NLTK, SpaCy).
• Mathematical & Statistical Knowledge: Strong understanding of statistical modeling, probability theory, and mathematical optimization techniques used in machine learning.
• Model Deployment & Automation: Experience with deploying machine learning models into production environments using platforms such as AWS SageMaker or Azure ML, GCP AI, or similar. Familiarity with
• MLOps practices is an advantage.
• Code Review & System Design: Experience in code review, design optimization, and ensuring quality in large-scale AI/ML systems. Understanding of distributed computing and parallel processing is a plus.

Soft Skills & Behavioural Qualifications:

• Must be a good team player and self-motivated to achieve positive results
• Must have excellent communication skills in English.
• Exhibits strong presentation skills with attention to detail.
• It’s essential to have a strong aptitude for learning new techniques.
• Demonstrates a high degree of reliability, integrity, and trustworthiness
• Ability to manage time, displays appropriate sense of urgency and meet/exceed all deadlines
• Ability to accurately process high volumes of work within established deadlines.