Job Description

Lead Data Scientist

Key Responsibilities-

• Background in Computer Science/Computer Applications or any quantitative discipline (Statistics, Mathematics, Economics/Operations Research etc.) from a reputed institute.
• 6-10 years of experience using analytical tools/languages like Python on large-scale data
• Must have Semantic modelling & NER experience
• Experience working with pre-trained models, awareness of state-of-art in embeddings and applicability for use cases
• Must have strong experience in NLP/NLG/NLU applications using any popular Deep learning frameworks like PyTorch, Tensor Flow, BERT, Langchain and GPT (or similar models) Open CV.
• Must have exposure to Gen AI models (LLMs) like Mistral, Falcon, Llama 2, GPT 3.5 & 4, Prompt Engineering
• Must have worked using Azure services for ML & GenAI projects.
• Demonstrated ability to engage with client stakeholders at multiple levels and provide consultative solutions across different domains
• Deep knowledge of techniques such as Linear Regression, gradient descent, Logistic Regression, Forecasting, Cluster analysis, Decision trees, Linear Optimization, Text Mining etc.
• Strong understanding of integrating NLP models into business workflows. Prospect should have exposure to project initiation to business impact creation in at least one project.

Required Experience-

• Total work experience of 7+ years, 4+ years in Advanced NLP, 1-year experience in GenAI
• Ability to guide and mentor teams of associates on solution development and approaches
• Broad knowledge of fundamentals and state-of-the-art in NLP and machine learning
• Coding skills in one or more programming languages such as Python, SQL
• Expert / high level of understanding on language semantic concepts & data standardization
• Proven track record of successful models and practical implementation
• Hands-on experience with popular ML frameworks such as TensorFlow
• Experience with application development practices at scale, from problem definition to deployment.
• Familiarity with any Cloud services such as AWS, Sage Maker etc. is an added advantage.
• Develop and apply Statistical Modelling techniques (e.g Bayesian models and deep neural networks), optimization methods, and other ML techniques to different applications.
• Knowledge in Machine Learning techniques in entity resolution, common speech products or text search domain.