Company:
Dale Workforce Solutions
Location: Thousand Oaks
Closing Date: 01/12/2024
Hours: Full Time
Type: Permanent
Job Requirements / Description
The Global Quality Analytics & Innovation (GQAI) team leads the digital transformation and innovation effort throughout Client’s Quality organization. We are at the forefront of developing and rolling out data-centric digital tools, employing automation, AI, and generative AI to drive end-to-end quality transformation.
We are seeking an experienced, highly motivated data scientist with a passion for AI and automation product development to join our team. The successful candidate will have the chance to leverage their skills to develop software products for internal stakeholders, generate actionable insights from data, and implement and monitor Client/GenAI models. This may include, but is not limited to, the following:
- Collaborate with cross-functional teams and stakeholders to create and manage digital products across various stages of development
- Develop, integrate, and optimize Machine Learning and Generative AI solutions with a focus on creating modular, reusable code
- Analyze and interpret enterprise data and model performance to unlock insights and monitor data & model quality
- Partner with business stakeholders to communicate key concepts and identify opportunities for process improvements
- Make connections between use-cases to enable efficiency and scale impact across the organization
Preferred Skills:
- Doctorate degree in computer science, mathematics, computer/electrical engineering, or a related discipline, or Master’s degree in any of the aforementioned disciplines and 3 years of experience
- 4+ years' experience in machine learning algorithms and techniques, both technically (how to use) and conceptually (where and why to use)
- Advanced expertise in Python and experience with relevant Client/GenAI libraries (e.g., Scikit-learn, LangChain, LlamaIndex)
- Advanced informatics and data science skills, including strong foundational knowledge of Natural Language Processing (NLP) and Large Language Models (LLMs)
- General understanding of MLOps and DevOps practices and tools (e.g., MLflow, version control, package development, CI/CD, etc.)
- Familiar with cloud computing environments and infrastructure such as Databricks and AWS (S3, DynamoDB, Lambda, Bedrock)
- Understanding of API development and deployment, such as FastAPI and RestAPI
- Experience in with business intelligence and visualizations tools such as Tableau, Streamlit, and Dash
- Quick learner, organized, and detail-oriented
- Exceptional communication skills, both written and verbal, with an ability to adjust communication style based on audience
Preferred Traits:
- Passion for Client and GenAI products and techniques with an understanding of where, why, and how to use them
- Intellectual curiosity with ability to learn new concepts, scripts, and methods
- Ability to manage multiple competing priorities simultaneously
- Ability to deliver work in an organized, and on-time fashion
- Ability to work in highly collaborative, cross-functional environments
Experience in the biotechnology industry is NOT required.
We are seeking an experienced, highly motivated data scientist with a passion for AI and automation product development to join our team. The successful candidate will have the chance to leverage their skills to develop software products for internal stakeholders, generate actionable insights from data, and implement and monitor Client/GenAI models. This may include, but is not limited to, the following:
- Collaborate with cross-functional teams and stakeholders to create and manage digital products across various stages of development
- Develop, integrate, and optimize Machine Learning and Generative AI solutions with a focus on creating modular, reusable code
- Analyze and interpret enterprise data and model performance to unlock insights and monitor data & model quality
- Partner with business stakeholders to communicate key concepts and identify opportunities for process improvements
- Make connections between use-cases to enable efficiency and scale impact across the organization
Preferred Skills:
- Doctorate degree in computer science, mathematics, computer/electrical engineering, or a related discipline, or Master’s degree in any of the aforementioned disciplines and 3 years of experience
- 4+ years' experience in machine learning algorithms and techniques, both technically (how to use) and conceptually (where and why to use)
- Advanced expertise in Python and experience with relevant Client/GenAI libraries (e.g., Scikit-learn, LangChain, LlamaIndex)
- Advanced informatics and data science skills, including strong foundational knowledge of Natural Language Processing (NLP) and Large Language Models (LLMs)
- General understanding of MLOps and DevOps practices and tools (e.g., MLflow, version control, package development, CI/CD, etc.)
- Familiar with cloud computing environments and infrastructure such as Databricks and AWS (S3, DynamoDB, Lambda, Bedrock)
- Understanding of API development and deployment, such as FastAPI and RestAPI
- Experience in with business intelligence and visualizations tools such as Tableau, Streamlit, and Dash
- Quick learner, organized, and detail-oriented
- Exceptional communication skills, both written and verbal, with an ability to adjust communication style based on audience
Preferred Traits:
- Passion for Client and GenAI products and techniques with an understanding of where, why, and how to use them
- Intellectual curiosity with ability to learn new concepts, scripts, and methods
- Ability to manage multiple competing priorities simultaneously
- Ability to deliver work in an organized, and on-time fashion
- Ability to work in highly collaborative, cross-functional environments
Experience in the biotechnology industry is NOT required.
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