AI Data Scientist

4 weeks ago

Cherry Hill, United States CareerBuilder Full time

Generative AI Data Scientist

Summary:

We're seeking a highly innovative Data Scientist to lead the development of advanced Generative AI (GenAI) applications at our company. This role is ideal for someone who combines analytical skills, technical expertise, and creative vision to convert complex data into actionable insights and groundbreaking AI solutions. You will be at the helm of initiatives involving Large Language Models (LLMs), Foundation Models (FMs), Retrieval-Augmented Generation (RAG) applications, and the fine-tuning of Open LLMs, crafting AI-driven solutions to real-world challenges.

Key Responsibilities:

Model Development: Leverage LLMs, FMs, and other AI technologies to analyze extensive datasets, develop predictive models, and uncover key insights.

Cross-functional Collaboration: Work alongside Machine Learning Engineers, business analysts, and stakeholders, ensuring data science aligns with and accelerates our business objectives.

Experimentation and Testing: Employ an experimentation mindset with A/B testing to validate model predictions, optimize performance, and confirm AI application reliability.

Data Processing, Analysis and Management: Oversee data collection, preprocessing, and management, maintaining data integrity for model training.

Innovative AI Solutions: Keep abreast of AI, Client, and GenAI advancements to continually refine our applications and maintain our competitive edge.

Insights and Recommendations: Provide strategic, data-driven insights and recommendations to inform high-level business strategies.

Mentorship: Foster a culture of learning and innovation, sharing best practices in data science and AI with the team.

Qualifications:

A bachelor's or master's degree in computer science, Data Science, Statistics, or related field.

Over 5 years of experience in data science, demonstrating the application of Client and AI technologies in business contexts.

Deep expertise in statistical analysis, predictive modeling, and Client algorithms, especially with LLMs and FMs.

Proficiency in Python or R and Client frameworks like TensorFlow or PyTorch.

Extensive experience in data manipulation, analysis, and visualization with large datasets.

Knowledge of cloud computing platforms, ideally AWS, and familiarity with data processing and Client services.

Experience with MLOps practices, covering the entire lifecycle from model development to deployment and monitoring.

Exceptional problem-solving capabilities, an innovative mindset, and the ability to excel in a fast-paced environment.

Excellent communication skills, capable of translating complex data insights into clear, actionable business directives.

Preferred Qualifications:

PhD in Computer Science, Data Science, Statistics, or a related field.

Familiarity with the latest GenAI technologies and methodologies, including prompt engineering and model fine-tuning.

Hands-on experience with database technologies, particularly VectorDBs, and a comprehensive understanding of the data infrastructure needed to support AI applications.

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