- You will help our clients solve real-world problems by tracing the data-to-insights lifecycle:
- Understand business problems, making sense of the data landscape & footprint, performing a combination of exploratory, Machine Learning & Advanced Analytics on textual data
- Create, experiment with and deliver innovative solutions in a consultative mindset to client stakeholders using textual data
- Guide team of analysts to offer exceptional solutions to clients, across domains.
- 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 modeling & 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.
- 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 considered a plus
- 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
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Description
About the Lead Data Scientist (NLP) Job Role
Key Responsibilities for Lead Data Scientist (GenAI & NLP)