Faire leverages machine learning and data insights to revolutionize the wholesale industry, enabling local retailers to compete against giants like Amazon and big box stores. The role aims to develop ML systems to activate new retailers, increase their engagement, and drive increased purchasing through personalized marketing and recommendations.
Requirements
- 5+ years of industry experience using machine learning to solve real-world problems
- Experience with relevant business problems (personalization, incentives, e-commerce, CRM)
- Experience with relevant technical methods (unsupervised learning, NLP, LLMs, causal ML)
- Strong programming skills
- An excitement and willingness to learn new tools and techniques
- The ability to contribute to team strategy and to lead model development without supervision
- Experience as a tech lead, mentoring other data scientists / machine learning engineers
Responsibilities
- Develop ML systems that help activate new retailers and increase their engagement.
- Build ML systems to re-engage retailers through personalized marketing.
- Develop intelligent recommendations that identify gaps in retailers' product assortments to drive increased purchasing.
- Drive data science strategy and execution within Retailer Growth.
- Use ML/AI to extract insights about retailers that can be used to personalize their first run experience at scale.
- Optimize marketing and incentive spend through targeting and personalization.
- Use experimentation and causal inference methods to measure the effectiveness of spend levers.
Other
- Drive data science vision, strategy, and execution within Retailer Growth, using ML solutions to activate and engage more retailers on the platform
- Work with cross-functional stakeholders to develop end-to-end product solutions
- Mentor senior data scientists on Retailer Growth
- Strong communication skills and the ability to work in a highly cross-functional team
- Highly recommended: Master’s or PhD in Computer Science, Statistics, or related STEM fields
- Previous experience in e-commerce personalization or incentive optimization
- Experience as a tech lead manager
- Effective January 2025, Faire employees will be expected to go into the office 2 days per week on Tuesdays and Thursdays. Additionally, hybrid in-office roles will have the flexibility to work remotely up to 4 weeks per year.
- Faire provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity or gender expression.
- Faire is committed to providing access, equal opportunity and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. Accommodations are available throughout the recruitment process and applicants with a disability may request to be accommodated throughout the recruitment process. We will work with all applicants to accommodate their individual accessibility needs. To request reasonable accommodation, please fill out our Accommodation Request Form (https://docs.google.com/forms/d/e/1FAIpQLSczpI9me7nYKhunSC6AlagHKv75LHqfi-Qi2TP_3dpin0Uc9Q/viewform) (https://bit.ly/faire-form)
