Principal Data Science Engineer

$140,000 - $140,000/Yr

Unclassified - Conshohocken, PA

Full-time - Senior

Remote - Conshohocken, PA

About the position

The Principal Data Science Engineer will be responsible for developing cost-effective tools and support structures for data analysis, including data cleaning, feature selection, and feature engineering. This role involves collaborating with multidisciplinary teams to implement models across various clients, presenting findings to stakeholders, and preparing reports for executive leadership. The engineer will also lead data science projects, mentor junior team members, and evaluate external AI services for potential integration into solutions.

Responsibilities

• Build cost-effective tools and support structures for data analysis.
• Perform data cleaning, feature selection, and feature engineering.
• Organize experiments following best practices.
• Collaborate with multidisciplinary teams to implement models for clients.
• Present findings to stakeholders to drive improvements and solutions.
• Prepare reports for executive leadership communicating trends and predictions.
• Apply for patents and serve on the reviewing committee.
• Drive development of machine learning, deep learning, and statistical modeling for analytics.
• Lead implementation of NLP techniques to extract insights from unstructured data.
• Serve as a spokesperson for the business at tech/industry conferences.
• Lead data science projects to deliver impactful business outcomes.
• Partner with external entities to develop strategic alliances.
• Evaluate external AI services for building AI-driven solutions.
• Mentor and guide Junior Data Scientists in tools and methodologies.
• Serve as a scrum master, planning and tracking tasks with Jira.

Requirements

• Bachelor's degree in Computer Science, Engineering, Data Science, Integrated Innovation or a related field and six years of experience in the job offered, or a Master's degree in the same fields with four years of experience.
• Demonstrated experience with machine learning techniques such as clustering, decision trees, and neural networks.
• Proficiency in programming and analytics languages, particularly Python and SQL.
• Experience with open-source machine learning and NLP libraries like Scikit-learn, TensorFlow, PyTorch, and others.
• Knowledge of CI/CD processes for ML models using AWS services.
• Experience deploying Large Language Models and managing graph data with advanced techniques.
• Familiarity with DevOps tools such as GIT, Splunk, and Jenkins.

Benefits

• Telecommuting allowed from anywhere in the U.S.