Lead Data Scientist

1 week ago

Bengaluru, India Straive Full time
Job Role- Lead Data Scientist(Gen AI)

Experience- 6 to 10 years

Location- Bangalore/Hyderabad

Mode- Hybrid (3 days WFO)

About Straive:

Straive is a market leading Content and Data Technology company providing data services, subject matter expertise, & technology solutions to multiple domains.

Data Analytics & Al Solutions, Data Al Powered Operations and Education & Learning form the core pillars of the company’s long-term vision. The company is a specialized solutions provider to business information providers in finance, insurance, legal, real estate, life sciences and logistics. Straive continues to be the leading content services provider to research and education publishers.

Data Analytics & Al Services: Our Data Solutions business has become critical to our client's success. We use technology and Al with human experts-in loop to create data assets that our clients use to power their data products and their end customers' workflows. As our clients expect us to become their future-fit Analytics and Al partner, they look to us for help in building data analytics and Al enterprise capabilities for them.

With a client-base scoping 30 countries worldwide, Straive’s multi-geographical resource pool is strategically located in eight countries - India, Philippines, USA, Nicaragua, Vietnam, United Kingdom, and the company headquarters in Singapore.

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 mind set to client stakeholders using textual data- Guide team of analysts to offer exceptional solutions to clients, across domains.

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.

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