Lead Data Scientist (remote)- Full Time

Title : Lead Data Scientist

Location : Seattle, WA

Experience : 10 Years

FTE Only

Remote will work but candidate should comfortable working in Pacific time zone.

Designs and implements data science solutions that are scalable, reliable, and performant, using tools and technologies such as Python, R, SQL, and machine learning frameworks.

Job Description:

Key Responsibilities: Lead and manage data science projects from ideation through to deployment, ensuring they meet business requirements and are delivered on schedule.Hands-on development of predictive models and machine learning algorithms using cloud platforms such as Azure, AWS, and Google Cloud Platform.Act as the primary point of contact for clients, understanding their challenges, proposing solutions, and maintaining strong relationships.Independently lead a team of data scientists and analysts, providing guidance and support to ensure professional growth and project success.Stay abreast of developments in AI/ML, especially Generative AI technologies, and evaluate their applicability to current and future projects.Ensure the technical feasibility and scalability of AI/ML solutions.

Conduct regular reviews and adjust project scopes, timelines, and technologies as needed.Communicate complex data-driven insights and the value of proposed solutions to non-technical stakeholders.

Requirements:

10-13 years of experience in data science, with a significant portion in a leadership role managing teams and projects.

Proven track record of building and deploying machine learning models and using AI/ML frameworks and services across Azure, AWS, and Google Cloud Platform.

Strong understanding of and experience with Generative AI applications and their use cases.

Excellent problem-solving skills with a client-oriented approach to project management.

Exceptional leadership skills with the ability to mentor and motivate team members.

Strong communication skills, capable of effectively interacting with both technical and non-technical stakeholders.

Master's or PhD in Computer Science, Data Science, Statistics, or a relevant field.

Preferred Qualifications: Certifications in Azure, AWS, or Google Cloud Data and Machine Learning services.Published research or active participation in the data science community through talks and conferences.

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