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Lead Data Scientist at atyeti | Jobyssey

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Lead Data Scientist

Lead Data Scientist

atyeti · 3 months ago

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Work mode: Remote
Seniority: Lead
Category: Data science
Experience: 6+ years

ai aws azure cloud data-science embeddings gcp generative-ai llm machine-learning prompt-engineering python

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vector-databases

Key Responsibilities

Design, build, and deploy scalable AI and Machine Learning models to solve complex business problems.
Develop predictive, classification, recommendation, and optimization models using structured and unstructured data.
Build and fine-tune Large Language Models (LLMs) and Generative AI applications for enterprise use cases.
Develop Retrieval-Augmented Generation (RAG) solutions and prompt engineering strategies.
Collaborate with cross-functional teams including business stakeholders, data engineers, and application developers to deliver AI-driven solutions.
Evaluate model performance and continuously optimize models for accuracy, scalability, and reliability.
Stay current with emerging AI technologies, research, and industry best practices.
Document models, methodologies, and deployment processes following enterprise standards.
Mentor junior data scientists and contribute to AI best practices within the team.

Required Qualifications

Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.
6+ years of experience as a Data Scientist or in a similar AI/ML role.
Strong hands-on experience in Artificial Intelligence and Machine Learning model development.
Experience building, training, validating, and deploying ML models in production environments.
Hands-on experience with Large Language Models (LLMs) and Generative AI technologies.
Experience with prompt engineering, embeddings, vector databases, and Retrieval-Augmented Generation (RAG).
Strong programming skills in Python.
Experience with ML libraries and frameworks such as Scikit-learn, TensorFlow, PyTorch, XGBoost, or similar.
Experience with SQL and data manipulation techniques.
Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
Strong analytical, problem-solving, and communication skills.