Senior Data Scientist

Dallas, IA - USA

Monthly Salary: Not Disclosed

Posted on: 30+ days ago

Vacancies: 1 Vacancy

The job posting is outdated and position may be filled

Job Summary

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