Data Scientist in Bengaluru, India is listed on Jobeax. Browse 30,000+ vacancies available.
Experience Level: 2-5 years Location: Bengaluru Education: Bachelor's or Master's degree in Computer Science, Data Science, Mathematics, Statistics, or related fields. A strong academic pedigree is highly preferred.
Overview: We are seeking a talented and motivated Data Scientist to join our team. The ideal candidate will have 2-5 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.
Document workflows, methodologies, and findings for both technical and non-technical stakeholders.
Key Skills and Qualifications:
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).
General Skills:
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.
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