Bangalore Sr_ Data Scientist Bang

We are seeking a talented and motivated Data Scientist to join our team. The ideal candidate will have 6-10 years of hands-on experience in the development and deployment of Machine Learning (ML) projects. Exposure to Computer Vision and Natural Language Processing (NLP), especially Large Language Models (LLMs), will be a significant advantage.

Key Responsibilities:
• Develop, deploy, and optimize ML models for prediction and forecasting tasks on tabular/text datasets.
• Collaborate with cross-functional teams to understand business requirements and translate them into data-driven solutions.
• Perform data preprocessing, feature engineering, and exploratory data analysis (EDA) to support model development.
• Build and deploy end-to-end ML pipelines, including model training, evaluation, and serving in production environments.
• Monitor and maintain deployed models to ensure robustness, scalability, and performance over time.
• Implement feedback loop into prediction.
• Drive innovation: Explore, experiment with, and integrate cutting-edge ML techniques and frameworks into projects.
• Experience in Computer Vision, NLP, and LLMs in production environment will be a plus.
• Exposure to data volume extremes (high volume, constrained volume) will be a plus.
• Document workflows, methodologies, and findings for both technical and non-technical stakeholders.

6-10 years

Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, Statistics, or related fields. A strong academic pedigree is highly preferred.

Core Expertise:

• Proficiency in Python and popular ML libraries such as Scikit-learn, TensorFlow, or PyTorch.
• Strong understanding of supervised and unsupervised ML algorithms.
• Hands-on experience with model deployment tools such as Docker, Flask, FastAPI, or cloud-based ML services (AWS SageMaker, GCP Vertex AI, etc.).
• Proficiency in working with structured/unstructured data, SQL.\

Added Advantage:

• Experience in Computer Vision (e.g., OpenCV, YOLO, or related frameworks).
• Exposure to NLP/LLMs (e.g., Hugging Face, GPT, or BERT).
• Familiarity with MLOps practices, CI/CD pipelines for ML, and model monitoring (MLFlow).

• Strong problem-solving skills and attention to detail.
• Excellent communication skills to convey technical concepts to diverse audiences.
• Ability to work in a fast-paced environment and manage multiple priorities effectively.