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Data Scientist
4 weeks ago
Experience:6+ Years
Location: Bengaluru, Hyderabad
Notice Period: Immediate
Position Type: Full-time
Job Description
As a Data Scientist, you will play a crucial role in designing and implementing scalable, efficient, and automated processes for large-scale data analysis, machine-learning model development, validation, and deployment. You will collaborate closely with cross-functional teams to drive innovation and deliver impactful solutions to complex business problems.
Responsibilities:
Design and build scalable, efficient, and automated processes for large-scale data analysis, machine-learning model development, validation, and serving.
Conduct experiments to improve model performance and efficiency.
Participate in brainstorming sessions to generate innovative ideas and solutions.
Effectively communicate complex technical concepts to both technical and non-technical stakeholders.
Work independently and collaboratively with internal and external teams to drive projects forward.
Requirements:
Ph.D. with 4 years of work experience or Master's degree with 6 years of work experience in Computer Science, Machine Learning, Natural Language Processing, or related field.
8+ years of experience in AI, ML, DL, and Reinforcement Learning, with a focus on research in AI/ML/DL technologies.
Extensive knowledge and practical experience with deep learning, reinforcement learning, and Graph Neural Networks.
Solid understanding of AI model architecture, training paradigms, fine-tuning processes, and optimization techniques.
Proven experience with large language models (LLMs) such as GPT-3, GPT-4, or similar.
Strong expertise in Python, PostgreSQL, and deep learning frameworks such as TensorFlow, PyTorch, MXNet, and Keras.
Experience with recommender systems and context-aware machine learning frameworks (5+ years).
Advanced foundation in Linear Algebra, Calculus, and Statistics.
Experience in applying both sequence-based and traditional methods to recommender problems.
Proficiency in data mining, data transformation, and database building (ETL, SQL OLAP, Teradata, Hadoop).
Knowledge of cloud-native computing, DevOps practices, and containerization technologies such as Docker and Kubernetes.
Strong analytical and problem-solving skills with the ability to analyze large-scale datasets and derive meaningful insights.
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