Required qualifications, capabilities, and skills
- Formal training or certification on data science concepts and 2+ years applied experience
- Experience with Shell Scripting, Jupyter notebook/Lab, SQL, PySpark, and AWS Cloud Services is required.
- Proficient in Python with hands-on experience in Machine learning and Deep learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., NumPy, Scikit-Learn, Pandas). Experience with Jupyter Notebook/Lab is essential.
- Extensive experience in Natural Language Processing (NLP) or Large Language Models (LLM),or Computer Vision and other machine learning techniques, including classification, regression algorithms.
- Solid Understanding of algorithms in machine learning, AI, and neural network, including Large Language Models (LLM) and Generative AI as well as familiarity with state-of-the-art practices and advancements in these domains.
- Proficient in both basic and advanced exploratory data analysis (EDA), with an understanding of the limitations and implications of different methodologies.
- Ability to set the analytical direction for projects, transforming vague business questions into structured analytical plans. You possess strong cognitive and communication skills, characterized by clear and articulate expression. You excel at identifying core issues, bringing order to chaos, synthesizing insights, and driving decisive outcomes.
Preferred qualifications, capabilities, and skills
- Familiarity working with one or more LLM frameworks like langchain/llamaindex/langgraph/crewAI
- Familiarity with one or more python API frameworks like FastAPI/Flask/Django