Data Scientist

Job Overview

We are iCIMS Talent Cloud AI, an agile team of product people, data scientists and software engineers, who created a collaborative environment centered around passion for people and their careers, as well as data science, high-performance software, and user experiences. Our culture feeds from innovation, engineering excellence and owning the outcomes for our stakeholders.

As a Data Scientist, you will play a crucial role in AI engineering for the iCIMS Talent Cloud. You will assist with building Natural Language Processing (NLP) models and statistical analysis using emerging components and technologies. Experience in the HR domain is a plus.

For this role you must have demonstrated machine learning experience and strong software skills coupled with a sound theoretical base in model training and optimization. If you have deeper experience or a stronger academic background, please apply as we may have some flexibility.

Hybrid/remote work in Ireland, focused near Dublin. The team meets weekly in the iCIMS office at Dogpatch Labs.

Responsibilities

• Build, train and deploy AI/ML natural language models independently.
• Evaluate models qualitatively and quantitatively using automated and statistical tools.
• Extract, clean and transform text and structured data.
• Define and implement detailed work for an AI task or user story.
• Use defined practices for reproducible, testable, ethical, efficient, and production ready AI.
• Ensure all work meets responsible AI practices.
• Document and present results to peers and leaders.
• Monitor production results and investigate reported issues.
  
  

Qualifications

• Bachelor’s degree in Data Science, Computer Science, Statistics, or a related field OR equivalent learning and experience.
• 2+ years experience implementing AI/ML models in products.
• Proficient with Python and data science frameworks.
• Excellent problem-solving and analytical skills.
• Effective communication and interpersonal skills. Articulates thoughts and ideas clearly, concisely.