Conexiom · 1 day ago

Lead Data Scientist

United States

Full-time

Remote

Senior Level

5+ years exp

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Responsibilities

Serve as the technical lead in defining and refining our modeling approach, balancing traditional machine learning methods with Large Language Models (LLMs) to achieve optimal results.

Drive architectural decisions for deep learning models, working closely with engineers to ensure scalability, efficiency, and maintainability.

Lead by example, working hands-on with datasets, EDA, models, and implements in production, spending approximately 90% of your time on direct technical work.

Offer thought leadership by deeply analyzing complex problems, identifying underlying patterns, and critically evaluating solutions for data science challenges.

Mentor Senior Data Scientists and other team members, fostering technical growth and promoting best practices in model development and deployment.

Collaborate with the Chief Data Scientist to align data science strategy with business objectives and provide input on high-level goals and projects.

Qualification

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Machine LearningLarge Language ModelsDeep LearningPythonTensorFlowPyTorchScikit-LearnData ScienceTechnical LeadershipSaaS EnvironmentStatistical AnalysisBusiness Automation

Required

Master’s or Ph.D. degree in Computer Science, Data Science, Machine Learning, Statistics, or a related field.

5+ years’ experience in developing and deploying machine learning models, including at least 2 years in technical leadership capacity.

Expertise in both traditional ML techniques and experience with Large Language Models, including hands-on experience with fine-tuning and application of LLMs.

Advanced knowledge of deep learning architectures and the ability to make architectural decisions that impact performance and scalability.

Strong proficiency in Python, along with experience in machine learning libraries and frameworks such as TensorFlow, PyTorch, and Scikit-Learn.

Ability to translate business problems into structured data science tasks and effectively communicate findings and recommendations.