Primary role is to analyze data and build machine learning models using GCP services like Vertex AI and BigQuery. Lead a team of Data scientists guide and monitor for efficiency and productivity
- Key responsibilities include the end-to-end project lifecycle from defining business problems and collecting data to deploying and monitoring models while collaborating with data engineers and business stakeholders to drive data-driven decisions.
- Data analysis and visualization: Analyze large datasets to identify trends patterns and insights. Create data visualizations and reports to communicate findings to stakeholders.
- Model development: Design develop and implement advanced statistical and machine learning models for tasks like forecasting classification and optimization using GCP tools and services.
- Data pipeline and workflow management: Collaborate with data engineers to design and optimize data pipelines and build their own data processing transformation and analysis pipelines.
- Model deployment and monitoring: Deploy machine learning models into production environments on GCP and continuously monitor their performance
- Extensive hands-on experience of working on challenging AI/ML projects in an industry setting from ideation to deployment
- Highly proficient in programming (Python SQL) and expert user of various AI/ML frameworks (scikit-learn TensorFlow PyTorch etc.) - its a 100% hands-on role
- Strong knowledge of ML foundations Transformers LLM architecture prompting and fine tuning of LLMs
- 8 years of experience in data science and machine learning algorithms building and deploying models and associated with entire lifecycle of model analysis/building/Deployment/assessment. Must have worked on 2/3 production projects as a Data Scientist
- 3 years of a Tech or DS lead role leading programs and/or technical teams
- Good hands-on experience with Vertex AI ML models Vector databases RAG.
- Experience working with business and key stakeholders to understand model requirements and build accordingly
- Strong commitment to work and ownership
- Demonstrable impact of work on the business bottomline (money saved efficiency gain better security etc.)
- Familiarity with at least one public cloud services (GCP AWS Azure) preference will be given to GCP and Vertex AI
- Design development and deployment of ML pipelines in the cloud
- Experience with MLOps and operationalizing models in production lifecycle management of models
- Data governance: Adhere to data security and compliance standards.
Behavioral skills:
- Strong Analytical and problem-solving skills
- Fast learner and adopter of new technologies
- Open to feedback and willing to work on it
- A team player willing to wear different hats as the situation demands
- Knows how to collaborate with various stakeholders understands their requirements and translates it for the team
- Strong communicator within and outside the team
Primary role is to analyze data and build machine learning models using GCP services like Vertex AI and BigQuery. Lead a team of Data scientists guide and monitor for efficiency and productivity Key responsibilities include the end-to-end project lifecycle from defining business problems and co...
Primary role is to analyze data and build machine learning models using GCP services like Vertex AI and BigQuery. Lead a team of Data scientists guide and monitor for efficiency and productivity
- Key responsibilities include the end-to-end project lifecycle from defining business problems and collecting data to deploying and monitoring models while collaborating with data engineers and business stakeholders to drive data-driven decisions.
- Data analysis and visualization: Analyze large datasets to identify trends patterns and insights. Create data visualizations and reports to communicate findings to stakeholders.
- Model development: Design develop and implement advanced statistical and machine learning models for tasks like forecasting classification and optimization using GCP tools and services.
- Data pipeline and workflow management: Collaborate with data engineers to design and optimize data pipelines and build their own data processing transformation and analysis pipelines.
- Model deployment and monitoring: Deploy machine learning models into production environments on GCP and continuously monitor their performance
- Extensive hands-on experience of working on challenging AI/ML projects in an industry setting from ideation to deployment
- Highly proficient in programming (Python SQL) and expert user of various AI/ML frameworks (scikit-learn TensorFlow PyTorch etc.) - its a 100% hands-on role
- Strong knowledge of ML foundations Transformers LLM architecture prompting and fine tuning of LLMs
- 8 years of experience in data science and machine learning algorithms building and deploying models and associated with entire lifecycle of model analysis/building/Deployment/assessment. Must have worked on 2/3 production projects as a Data Scientist
- 3 years of a Tech or DS lead role leading programs and/or technical teams
- Good hands-on experience with Vertex AI ML models Vector databases RAG.
- Experience working with business and key stakeholders to understand model requirements and build accordingly
- Strong commitment to work and ownership
- Demonstrable impact of work on the business bottomline (money saved efficiency gain better security etc.)
- Familiarity with at least one public cloud services (GCP AWS Azure) preference will be given to GCP and Vertex AI
- Design development and deployment of ML pipelines in the cloud
- Experience with MLOps and operationalizing models in production lifecycle management of models
- Data governance: Adhere to data security and compliance standards.
Behavioral skills:
- Strong Analytical and problem-solving skills
- Fast learner and adopter of new technologies
- Open to feedback and willing to work on it
- A team player willing to wear different hats as the situation demands
- Knows how to collaborate with various stakeholders understands their requirements and translates it for the team
- Strong communicator within and outside the team
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