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. Minimum of Bachelor's Degree in Computer Science, Computer Engineering, Machine Learning / Data Science / AI or related disciplines
. Able to understand and apply a range of AI/ML techniques for regression and classification
. Familiar with popular python packages ( e.g. pandas, matplotlib, scikit-learn, XGBoost, NLTK, spaCy )
. Understanding of LLM concepts (e.g. context windows, embeddings, chunking, token management) and architectures (e.g. RAG)
. Experience with context engineering techniques and prompt optimization strategies
. Proficient in git, SQL
. Proficient in Business Intelligence tools (e.g. Tableau, Qlik, MS PowerBI, Microstrategy)
Job ID: 150548383
Skills:
Microsoft Power Bi, Tableau, Sql, Git, Nltk, Pandas, Matplotlib, XGBoost, Qlik, Python, scikit-learn, spaCy, Microstrategy
Skills:
geospatial data , Algorithms, Tensorflow, Pytorch, XGBoost, Python, AWS, Machine Learning, Apis, Time Series, Pandas, Gcp, Clustering, Containers, Azure, scikit-learn, Linear Programming, reinforcement learning, heuristics, real-time analytics platforms, cloud platforms, Classification, Regression, Optimization Techniques, Statistics
Skills:
Machine Learning, Natural Language Processing, Sql, Python, knowledge graphs, personalisation engines, retrieval-augmented generation, data science libraries, time-series forecasting, recommendation systems, MLOps tooling, large language models
Skills:
Agile Project Management, Pytorch, Python Programming, LangChain, large data handling, data visualization packages, boosting models, GenAI solutions, transformer models, AI applications
Skills:
Tensorflow, Git, Pytorch, Spark, Python, Sql, git-flow
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