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Data Scientist

Shanghai, China

Who We Are

Born from a mission to make prescription eyewear affordable and accessible to everyone, Zenni Optical has been changing the way people see the world since 2003. With complete prescription pairs for adults and kids starting at under $10, we’ve grown into a global brand with over 51 million pairs of glasses sold — and counting!

Based in the San Francisco Bay Area, we're proud to be the Official Eyewear of the San Francisco 49ers, Boston Celtics, Monster Jam, Ghost Gaming, TSM, Major League Pickleball and more. We've also partnered with tastemakers and designers like Chase Stokes, Jrue Holiday, and George and Claire Kittle to bring our brand to life in bold, meaningful ways.

Innovation is at the heart of everything we do at Zenni — from our revolutionary EyeQLenz™ with Zenni ID Guard™  glasses to our cutting-edge VR Vision Screener, we're constantly exploring new ways to improve vision and enhance lives. For more information, please visit zenni.com/press.

Candidate safety is important to us. Please note that all official communication will only be sent from @zennioptical.com addresses.

About the Role

Join Zenni Optical's AI & Machine Learning team as a Senior Staff Data Scientist, where you'll lead transformative initiatives that impact millions of eyewear customers worldwide. In this pivotal role, you'll drive innovation across computer vision, personalized experiences, and AI-powered solutions that directly influence revenue growth, customer retention, and operational efficiency.

As a technical leader, you'll combine deep machine learning expertise with mentorship responsibilities, spending most of your time on hands-on technical work while guiding junior data scientists. You'll own the complete lifecycle of high-impact ML projects from initial problem framing through production deployment and performance optimization.

This onsite position offers the unique opportunity to shape AI strategy at a leading eyewear company, working with cutting-edge ML infrastructure to solve complex challenges in computer vision, recommendation systems, and personalization at scale.

Responsibilities:

  • Own end-to-end ML project lifecycle from problem framing and data preparation through model deployment, monitoring, and performance optimization.
  • Develop advanced document understanding solutions using OCR and LLMs for automated processing workflows.
  • Design and implement personalized recommendation systems that drive product discovery and enhance customer experience.
  • Build sophisticated NLP and LLM-powered solutions for conversational AI and automated response generation.
  • Create predictive models for customer behavior analysis, demand forecasting, and personalization using advanced machine learning and statistical techniques.
  • Conduct rigorous experimentation and A/B testing to validate model performance and quantify business impact.
  • Monitor and optimize model performance in production environments, proactively identifying drift, bias, and improvement opportunities.
  • Establish robust ML system architecture and scalable deployment patterns for high-availability production systems.
  • Lead code reviews and enforce technical standards across the data science team.
  • Resolve complex modeling and statistical challenges, providing expert guidance on advanced techniques and methodologies.
  • Build data pipelines and analytics frameworks for both batch and real-time processing at scale.
  • Mentor and coach junior data scientists, providing technical guidance, career development support, and project leadership.
  • Partner with cross-functional stakeholders to translate business requirements into technical solutions and effectively communicate results to leadership.

Basic Qualifications: 

  • BS or MS in Computer Science, Applied Mathematics, or a related field.
  • 10+ years of data science experience with demonstrated progression to senior technical roles and proven track record of leading high-impact ML projects.
  • Solid Python programming skills and a solid software engineering foundation.
  • Expert-level proficiency in SQL with experience in data manipulation and analysis at scale.
  • Deep expertise in machine learning and statistics, including supervised/unsupervised learning, deep learning frameworks, and statistical modeling techniques.
  • Computer vision and NLP experience, particularly with document understanding.
  • Proven experience with recommendation systems design, implementation, and optimization.
  • Strong project and people leadership skills, with experience mentoring team members and driving cross-functional initiatives.
  • Excellent written and verbal communication skills, with ability to articulate complex technical concepts to diverse audiences.
  • Open-minded approach to problem-solving and curiosity to explore innovative AI solutions.

Preferred Qualifications:

  • Familiarity with cloud computing platforms, such as GCP, DataBricks.
  • Demonstrable project experience in deep learning applications with real-world impact.
  • Hands-on experience with production LLM-based applications, including deployment, fine-tuning, and optimization.
  • E-commerce or retail industry experience with understanding of recommendation and personalization challenges.
  • Deep learning specialization in computer vision or natural language processing.
  • Experience with real-time ML systems handling millions of users with low-latency requirements.
  • Familiarity with ML lifecycle management tools and ML platform development.

 

We look forward to hearing from you!

We strive to build a diverse team of individuals with a broad range of experience and perspectives. We encourage you to apply even if you don’t feel you meet all the qualifications.

Zenni Optical is an equal opportunity workplace and considers applications without regard to race, color, national origin, gender identity, sexual orientation, age, citizenship, marital status, disability, or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.

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