Data Scientist | Jaipur

Job Summary

We are seeking a highly skilled Data Scientist with strong expertise in Machine Learning and Python programming. The ideal candidate should be passionate about writing clean and efficient code, developing production-ready ML models, and solving complex business challenges using data. In addition.
This role is best suited for someone who thrives in coding-intensive environments, enjoys experimenting with algorithms, and can translate theoretical concepts into scalable ML and AI solutions.

Key Responsibilities

• Machine Learning Development: Design, build, and optimize classical ML models (regression, SVM, decision trees, random forests, gradient boosting, clustering, dimensionality reduction).
• Python Programming: Write clean, efficient, and scalable Python code, leveraging libraries such as NumPy, Pandas, Scikit-learn, etc.
• Deep Learning Systems: Implement and fine-tune deep learning models (CNNs, RNNs, Transformers) using frameworks like TensorFlow or PyTorch.
• Generative AI (Good Exposure Required): Work with LLMs, Transformers, GANs, VAEs; fine-tune and optimize GenAI models; contribute to prompt engineering and applied use cases.
• Data Management & Feature Engineering: Handle large datasets, perform preprocessing, augmentation, and feature engineering for ML workflows.
• Model Deployment & Monitoring: Deploy models into production and monitor performance, addressing issues like drift, bias, or overfitting.
• Coding Standards: Participate in code reviews, ensure best practices in coding, scalability, and maintainability of ML solutions.
• Collaboration: Work closely with cross-functional teams including engineers and product managers to integrate ML/GenAI solutions into real-world applications.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, Statistics, or related fields.

Primary Skills:

• Strong expertise in Machine Learning and Python programming.

• Good exposure to Generative AI (LLMs, Transformers, Prompt Engineering, Fine-tuning models).

• Experience with ML/DL frameworks such as TensorFlow, PyTorch, or Keras.

• Good mathematical/statistical foundation in probability, optimization, and modeling.

• Familiarity with deployment platforms (AWS SageMaker, Azure ML, GCP AI) and MLOps practices is an advantage.

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