Data Scientist II (AI)

TL;DR

Data Scientist II (AI): Analyzing, modeling, and optimizing AI technologies for an AI-driven search and shopping assistant with an accent on developing conversation-based, multimodal shopping experiences. Focus on measuring and improving multimodal conversational systems based on large language models, information retrieval, recommender systems, and knowledge graphs at hirify.global scale.

Location: Onsite in London, UK

Company

hirify.global is a large corporation building industry-leading language technology powering Rufus, their AI-driven search and shopping assistant.

What you will do

• Perform hands-on analysis and modeling of enormous multimodal datasets to develop insights into customer shopping journeys.
• Use statistical methods, machine learning, and data mining to create scalable solutions for optimizing shopping assistant systems.
• Design and analyze A/B tests and experiments to evaluate new features and model improvements.
• Develop metrics, dashboards, and reporting frameworks to monitor system performance and customer engagement.
• Build predictive models and conduct deep-dive analyses to identify opportunities for improving customer experience.
• Collaborate with Applied Scientists and Engineers to translate analytical insights into production systems.

Requirements

• Experience with machine learning/statistical modeling data analysis tools and techniques.
• Experience in an ML or data scientist role with a large technology company.
• Experience with data scripting languages (e.g., SQL, Python, R).
• Master's degree or above in Math, Statistics, Computer Science, or related science field.
• Ability to effectively communicate complex concepts through written and verbal communication.

Nice to have

• Experience with AWS services including S3, Redshift, Sagemaker, EMR, Kinesis, Lambda, and EC2.
• Experience in defining and creating benchmarks for assessing GenAI model performance.
• Experience working on multi-team, cross-disciplinary projects.

Culture & Benefits

• Inclusive culture that empowers employees to deliver the best results.
• Focus on discovering, inventing, simplifying, and building.
• Commitment to diversity, making recruiting decisions based on experience and skills.
• Equal opportunities employer, non-discriminatory based on protected veteran status, disability, or other legally protected status.