Primary Responsibilities:
- Analyze and interpret large datasets to extract meaningful insights
- Develop statistical models and machine learning algorithms to solve business problems
- Collaborate with cross-functional teams to understand data requirements and provide data-driven solutions
- Assist in designing and implementing data collection and data cleaning processes
- Perform exploratory data analysis to identify trends, patterns, and correlations
- Communicate findings and recommendations to stakeholders in a clear and concise manner
- Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so
Required Qualifications:
- Experience with large language models (LLMs) and natural language processing (NLP) techniques
- Basic knowledge of prompt engineering and AI model fine-tuning
- Solid knowledge of statistical analysis and machine learning techniques
- Solid understanding of data cleaning, preprocessing, and feature engineering
- Understanding of vector databases (e.g., Pinecone, FAISS, ChromaDB) for efficient similarity search and retrieval
- Proficiency in programming languages such as Python or R
- Familiarity with data visualization tools and techniques
- Familiarity with Langchain framework for developing applications with LLMs
- Proven excellent problem-solving and analytical skills
Preferred Qualifications:
- Undergraduate degree or equivalent experience
- Experience with SQL and working with relational databases
- Knowledge of cloud platforms and big data technologies (e.g., AWS, GCP, Azure)
- Familiarity with deep learning frameworks such as TensorFlow or PyTorch
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