DescriptionGEN AI Data Scientist Data Analytics
Responsibilities:
- Take ownership of AI/ML use cases from design and implementation to continuous enhancement.
- Act as a technical specialist in AI primarily focusing on Generative AI. Design and develop solutions to address various business challenges particularly those related to optimizing operational efficiency.
- Collaborate with other data engineers analysts data scientists product specialists and stakeholders to build well-crafted pragmatic and robust solutions that meet business requirements.
- Stakeholder management and engagement: proactively engage with stakeholders to understand their needs and translate them into technical requirements for AI/ML modeling.
- Maintain documentation of dataset curation modeling approach model performance code changes and workflows.
- Demonstrate a strong understanding of data privacy regulations such as PDPA and AI governance guidelines to ensure compliance.
- Foster an innovative and growth-oriented mindset continuously seeking opportunities to enhance AI/ML models and drive improvements across the organization.
Requirements:
- At least 35 years of experience in a data science role with relevant experience in AWS platform and/or Microsoft Copilot Studio.
- Bachelors degree in computer science or equivalent.
- Familiarity with techniques for Document Chunking Embedding and Information Retrieval for improving model accuracy and relevance.
- Expertise in Prompt Engineering for designing and managing effective prompts.
- Hands-on experience with AWS Bedrock including deploying solutions using foundation models and integrating them into scalable applications using APIs and orchestration tools.
- Experience in Agentic Flow for maximizing the utility of models including understanding user intent and context to drive meaningful interactions.
- In-depth knowledge of supervised and unsupervised ML models linear & logistic regression clustering tree-based models like random forest bagging and boosting models.
- Proficient in SQL Python and Spark.
- Proven experience in implementing MLOps practices on AWS.
- Familiar with Data Warehouses such as Redshift Hive and S3.
- Passionate about technology and always looking to upskill based on new developments in the AI space.
- AWS or Microsoft certifications will be a plus.
- Experience in the financial industry telecommunications or consulting is preferred.
DescriptionGEN AI Data Scientist Data AnalyticsResponsibilities:Take ownership of AI/ML use cases from design and implementation to continuous enhancement.Act as a technical specialist in AI primarily focusing on Generative AI. Design and develop solutions to address various business challenges par...
DescriptionGEN AI Data Scientist Data Analytics
Responsibilities:
- Take ownership of AI/ML use cases from design and implementation to continuous enhancement.
- Act as a technical specialist in AI primarily focusing on Generative AI. Design and develop solutions to address various business challenges particularly those related to optimizing operational efficiency.
- Collaborate with other data engineers analysts data scientists product specialists and stakeholders to build well-crafted pragmatic and robust solutions that meet business requirements.
- Stakeholder management and engagement: proactively engage with stakeholders to understand their needs and translate them into technical requirements for AI/ML modeling.
- Maintain documentation of dataset curation modeling approach model performance code changes and workflows.
- Demonstrate a strong understanding of data privacy regulations such as PDPA and AI governance guidelines to ensure compliance.
- Foster an innovative and growth-oriented mindset continuously seeking opportunities to enhance AI/ML models and drive improvements across the organization.
Requirements:
- At least 35 years of experience in a data science role with relevant experience in AWS platform and/or Microsoft Copilot Studio.
- Bachelors degree in computer science or equivalent.
- Familiarity with techniques for Document Chunking Embedding and Information Retrieval for improving model accuracy and relevance.
- Expertise in Prompt Engineering for designing and managing effective prompts.
- Hands-on experience with AWS Bedrock including deploying solutions using foundation models and integrating them into scalable applications using APIs and orchestration tools.
- Experience in Agentic Flow for maximizing the utility of models including understanding user intent and context to drive meaningful interactions.
- In-depth knowledge of supervised and unsupervised ML models linear & logistic regression clustering tree-based models like random forest bagging and boosting models.
- Proficient in SQL Python and Spark.
- Proven experience in implementing MLOps practices on AWS.
- Familiar with Data Warehouses such as Redshift Hive and S3.
- Passionate about technology and always looking to upskill based on new developments in the AI space.
- AWS or Microsoft certifications will be a plus.
- Experience in the financial industry telecommunications or consulting is preferred.
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