Data Scientist - Generative AI & Machine Learning
2 days ago
Description
• Analyze and interpret complex data from multiple sources, managing both structured and unstructured formats (text, audio, images, video, etc.). • Design, develop, and deploy generative AI solutions utilizing advanced technologies such as Retrieval-Augmented Generation (RAG), vector databases, and frameworks like LangChain and Hugging Face. • Leverage Optical Character Recognition (OCR) to convert diverse documents into searchable and editable formats, improving data accessibility. • Maintain and fine-tune existing AI models to optimize accuracy and performance, resolving any issues that may arise. • Develop new methodologies and optimize existing ones, pulling necessary data and building statistical and machine learning models to maximize business impact, particularly regarding profitability. • Solve complex analytical problems using large datasets, applying advanced statistical methods and conducting end-to-end analyses (data gathering, processing, analysis, and deriving actionable insights). • Present data-driven insights and recommendations to stakeholders at various levels through impactful visualizations and reports that support informed decision-making. • Lead and contribute to problem-solving efforts with a high degree of autonomy and flexibility. • Collaborate closely with data engineers, ML engineers, internal teams, and external clients. • Document methodologies, results, and processes clearly, ensuring reproducibility and knowledge sharing across the team. • Mentor and guide junior team members, including Data Scientists and ML Engineers.
Requirements
• Master’s degree in a quantitative discipline (e.g., Computer Science, AI, Machine Learning, Mathematics, Physics, Electrical Engineering, Industrial Engineering) or equivalent practical experience. • 3+ years of work experience in data analysis, data science, or a related field. • Proficiency with statistical software (e.g., Python, pandas) and database languages (e.g., SQL). • Experience with machine learning and data science libraries such as TensorFlow, Keras, PyTorch, and scikit-learn. • Expertise in Natural Language Processing (NLP), including text representation, semantic extraction techniques, and data modeling. • Be familiar with architecture design skills, especially with Proprietary and Open-Sourced LLMs (e.g., Llama, ChatGPT, Gemini, Claude). • Ability to adapt model architectures and apply transfer learning techniques to retrain models for specific domain needs. • Experience integrating AI agents into cross-functional teams to enhance products, services, and internal tools. • Familiarity with developing autonomous, multi-agent systems with capabilities for communication, learning, and collaboration. • Hands-on experience with cloud platforms (e.g., AWS) and CI/CD pipelines (e.g., GitLab). • 3+ years of production-level Python programming experience. • Applied experience with machine learning on large datasets. • Intermediate English
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