Education Requirements:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Applied Mathematics, Statistics, Linguistics, or a related field

Experience Requirements:

• 2+ years of experience in Data Science, focusing on NLP, prompt engineering, or deep learning

Other Requirements:

• Proficiency in Python and familiarity with AI frameworks and libraries (e.g., TensorFlow, PyTorch, Hugging Face)

• Strong understanding of NLP techniques and machine learning principles, including sentiment analysis, word embedding, text classification, and Transformer models (e.g., GPT, BERT)

• Experience with developing, optimizing, and evaluating prompts to improve AI model responses

• Experience with large language models (e.g., GPT-4, Llama3) and their applications in customer service or other domains

• Knowledge of data visualization tools and techniques to communicate complex data insights effectively

• Background in linguistics or computational linguistics

• Experience with agile development methodologies and big data platforms like Hadoop or Spark

• Excellent analytical, problem-solving, and communication skills

• Ability to work collaboratively in a team environment, manage multiple projects simultaneously, and document complex processes effectively

• Self-motivated with a passion for continuous learning and innovation in AI

Responsibilities:

• Prompt Engineering and Development

• Model Design and Implementation

• Benchmarking and Evaluation

• Collaboration and Communication

• Documentation and Research

Education Requirements:

• Bachelor’s or Master’s degree in Applied Mathematics, Statistics, Computer Science or another quantitative field

Experience Requirements:

• 2+ years of experience in Data Science or a related field, with a focus on building NLP/LLMs or Deep Learning models

Other Requirements:

• Strong programming skills in Python or other relevant programming languages

• Experience with machine learning libraries such as TensorFlow, PyTorch, or Keras

• Experience working with a variety of statistical models, including logistic regression, clustering, classification, SVMs, neural networks, Random Forest, CRF, Bayesian models, supervised/unsupervised learning, etc.

• Expertise in NLP techniques, including sentiment analysis, word embedding, part-of-speech (POS) tagging, topic modeling, text classification, machine translation, speech recognition, named entity recognition (NER), natural language generation (NLG), and other related techniques

• Experience with various deep learning techniques, including CNNs and RNNs, and a strong understanding of building and training these models for different applications. Familiarity with LMs and LLMs such as GPT, BERT, and Transformer models is highly desirable.

• Strong ability to rapidly comprehend and implement research papers related to AI, as well as remain informed of the latest advancements in NLP technologies

• Deep knowledge and experience in structured and unstructured data Information Extraction, Knowledge Information Retrieval, and Knowledge Representation

• Self-motivated and driven to satisfy intellectual curiosity through the pursuit of continuous learning and skill development

• Strong problem-solving and analytical skills

• Excellent communication and collaboration abilities

• Optional: Experience with big data platforms such as Hadoop or Spark

Responsibilities:

• Design and implement machine learning algorithms for NLP/LLMs or deep learning models at scale to meet business requirements

• Analyze large datasets and develop models that can be used to make predictions, generate responses or summaries, identify patterns etc.

• Develop and improve existing models to increase accuracy, efficiency, and effectiveness

• Work closely with cross-functional teams to identify and prioritize business problems, and develop solutions to address them

• Communicate findings and insights to stakeholders in a clear and concise manner

Experience Requirements:

• 3+ years of experience as a data scientist, preferably in a product development environment, with a focus on building NLP/LLMs or Deep Learning models

Other Requirements:

• Strong programming skills in Python or other relevant programming languages

• Experience with machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch)

• Deep understanding of statistical analysis, probability theory, and experimental design

• Experience with LLMs, deep learning, NLP and chatbot development

• Excellent communication skills, including the ability to explain complex concepts to technical and non-technical stakeholders

• Experience working with a variety of statistical models, including logistic regression, clustering, classification, SVMs, neural networks, Random Forest, CRF, Bayesian models, supervised/unsupervised learning, etc.

• Expertise in NLP techniques, including sentiment analysis, word embedding, part-of-speech (POS) tagging, topic modeling, text classification, machine translation, speech recognition, named entity recognition (NER), natural language generation (NLG), and other related techniques

• Experience with various deep learning techniques, including CNNs and RNNs, and a strong understanding of building and training these models for different applications. Familiarity with LMs and LLMs such as GPT, BERT, and Transformer models is highly desirable.

• Strong ability to rapidly comprehend and implement research papers related to AI, as well as remain informed of the latest advancements in NLP technologies

• Deep knowledge and experience in structured and unstructured data Information Extraction, Knowledge Information Retrieval, and Knowledge Representation

• Self-motivated and driven to satisfy intellectual curiosity through the pursuit of continuous learning and skill development

• Strong problem-solving and analytical skills

• Optional: Experience with large-scale data processing technologies (e.g., Hadoop, Spark) and distributed computing systems

Responsibilities:

• Design, develop and deploy machine learning models and algorithms for NLP/LLMs or deep learning models at scale to solve complex business problems

• Work with large datasets, perform data analysis and develop data pipelines to support model development

• Collaborate with Product & Engineering teams to integrate machine learning solutions into products and services

• Conduct experiments, test hypotheses, and perform statistical analysis to validate models and drive improvements

• Communicate findings and insights to stakeholders in a clear and concise manner

Education Requirements:

• Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field

Experience Requirements:

• Proven 5+ years of experience as an AI Analyst or similar role with a focus on data analytics and AI integration

Other Requirements:

• Experience in developing and deploying generative AI models is an advantage

• Good understanding of Prompt writing and evaluation

• Proficiency in Python and relevant AI libraries/frameworks (e.g., TensorFlow, PyTorch)

• Strong understanding of machine learning algorithms and natural language processing

• Solid experience with SQL for data manipulation and analysis

• Strong analytical and problem-solving abilities to derive actionable insights from complex datasets

• Excellent communication skills to translate technical concepts for varied audiences

• Proven ability to work effectively in cross-functional teams, promoting innovation and continuous improvement

• Capability to thrive in a fast-paced, dynamic environment while proactively identifying AI-driven improvements in chatbot functionalities

Responsibilities:

• Requirement Analysis

• Data Exploration and Analysis

• Feasibility Assessment

• Model Selection and Design

• Implementation and Deployment