Senior Data Scientist (AI)

TL;DR

Senior Data Scientist (AI): Designing, developing, and implementing AI-driven solutions to enhance the marketplace with an accent on generative AI applications for customer care and catalog management. Focus on developing, productionizing, and operating machine learning models and pipelines at scale.

Location: Hybrid (Paris, France)

Company

hirify.global is a global marketplace for refurbished devices, aiming to make tech reliable, affordable, and better than new while reducing environmental impact.

What you will do

• Own high-impact projects covering problem definition, metrics development, data extraction, model implementation, and presentation.
• Identify company problems and opportunities solvable through AI, develop evidence of validity (prototypes/MVP), and collaborate on product features.
• Hands-on development, productionization, and operation of machine learning models and pipelines at scale.
• Contribute to the internal AI community by promoting best practices and sharing work.
• Regularly present work internally to technical, engineering, and product stakeholders.

Requirements

• At least 6 years of industry experience in data science or related fields.
• Master’s or PhD in a quantitative discipline (Statistics, Economics, Sciences, or Engineering).
• Proven track record of leading impactful initiatives to develop data science products.
• In-depth understanding of the machine learning lifecycle, algorithms, and domains (e.g., time series prediction, NLP, computer vision, recommendation).
• Strong coding skills in Python and familiarity with software engineering principles.
• Experience in designing, prototyping, scaling, and launching data science products.
• Proven ability to mentor and develop scientists, engineers, and peers.
• Strong communication skills to convey complex technical concepts effectively.
• Curiosity, proactivity, humility, and team spirit.
• English: B2 required.

Culture & Benefits

• Mission-driven work environment with a positive impact on the planet.
• Hybrid work environment, with 2 remote days a week and 1 remote work week per quarter, plus 3 flex days.
• Employee Resource Groups, including mentorship programs, comprehensive accessibility policies, and cultural competency training.
• Commitment to diversity, equity, and inclusion principles.

Hiring process

• Call with Tech Talent Advisor.
• Homework assignment.
• Technical interview with Data Scientist and ML Engineer.
• Team Fit with Engineering Manager and Group PM.
• Cultural Fit interview.