Senior Applied AI/ML Scientist - Retailer Growth

Faire; San Francisco (CA); On-site; USD 196,000 - 269,500; Full time

Job summary

Faire leverages ML and data insights to revolutionize wholesale, helping local retailers compete with giants by activating and engaging more retailers on the platform. You will work on paid marketing and top‑of‑funnel acquisition, developing AI/ML systems for bidding, audience targeting, and content at scale.

As part of the Retailer Growth Data team, you’ll build ML models to optimize campaigns, experiment with causal inference, and drive faster feedback loops to improve conversion and

Qualifications

• 3+ years of industry experience applying ML to real‑world problems.
• Experience with e‑commerce problems and data
• Strong knowledge of LTV modelling, NLP, LLMs, and causal ML.
• Strong programming skills and willingness to learn new tools.
• Ability to design ML solutions without supervision.
• Strong cross‑functional communication skills.

Responsibilities

• Define data science vision, strategy, and execution within Retailer Growth using AI/ML solutions to activate and engage more retailers on the platform.
• Work with cross‑functional stakeholders to develop end‑to‑end product solutions.
• Extract deep behavioural insights using AI to automate AEO content creation and personalise the user landing experience.
• Optimize marketing capital allocation through sophisticated targeting and bidding optimisation strategies.
• Implement rigorous experimentation and causal inference frameworks to quantify growth impact.
• Engineer scalable solutions for two‑sided marketplace dynamics.

Skills

Machine learning

Programming

NLP

LLMs

Causal ML

E-commerce experience

Cross-functional communication

Data science strategy

Education

Master’s or Ph.D. in CS/Statistics or related STEM fields

Tools

Python

Job description

About Faire

Faire is a technology wholesale platform built on the belief that the future is local. Independent retailers around the globe collectively represent a multi‑hundred‑billion‑dollar wholesale market that has historically been fragmented and offline. At Faire, we’re using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe. Picture your favorite boutique in town — we help them discover the best products from around the world to sell in their stores. With the right tools and insights, we believe that we can level the playing field so businesses can grow and local communities can thrive.

We’re looking for smart, resourceful and passionate people to join us as we power the shop local movement. If you believe in community, come join ours.

About this role

Faire leverages the power of machine learning and data insights to revolutionize the wholesale industry, enabling local retailers to compete against giants like Amazon and big‑box stores. Our highly skilled team of Applied AI/ML Scientists specialise in developing algorithmic solutions for notification and recommender systems, advertising attribution, and LTV predictions. We are dedicated to building machine learning models that help our customers thrive.

As a member of the Retailer Growth Data team focusing on the paid marketing and top‑of‑funnel acquisition channels, you will develop AI/ML systems that help activate new retailers and increase their engagement. There are a wide range of ML opportunities in paid marketing optimisation, from bidding optimisation, search keyword intelligence, smart audience targeting to incrementality and efficiency estimation. With AI fast‑growing and changing every aspect of the world, AEO (Answer Engine Optimization) is the new chapter of growth that yet needs to be figured out, where there is a huge opportunity to leverage ML and LLM to create programmatic content at scale, build reinforcement learning systems for fast feedback loop, and optimise landing experience to improve conversion.

What you’ll do

• Drive data science vision, strategy, and execution within Retailer Growth, using AI/ML solutions to activate and engage more retailers on the platform
• Work with cross‑functional stakeholders to develop end‑to‑end product solutions
• Extract deep behavioural insights using AI to automate AEO content creation and personalise the user landing experience
• Optimize marketing capital allocation through sophisticated targeting and bidding optimisation strategies
• Implement rigorous experimentation and causal inference frameworks to quantify the impact of growth levers
• Engineer scalable solutions for complex challenges inherent to two‑sided marketplace dynamics

Qualifications

• 3+ years of industry experience using machine learning to solve real‑world problems
• Experience with relevant business problems (e‑commerce)
• Experience with relevant technical methods (LTV modelling, NLP, LLMs, causal ML, bidding optimisation)
• Strong programming skills
• An excitement and willingness to learn new tools and techniques
• The ability to design and implement ML solutions without supervision
• Strong communication skills and the ability to work in a highly cross‑functional team

Great to Haves

• Highly recommended: Master’s or Ph.D. in Computer Science, Statistics, or related STEM fields
• Previous experience in paid marketing, and/or growth team focusing on SEO and AEO optimisation
• Previous experience in LLMs and programmatic content generation

Salary Range

California: the pay range for this role is $196,000 to $269,500 per year. This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

Hybrid Faire employees currently go into the office 3 days per week on Tuesdays, Thursdays, and a third flex day of their choosing (Monday, Wednesday, or Friday). Additionally, hybrid in‑office roles will have the flexibility to work remotely up to 4 weeks per year. Specific Workplace and Information Technology positions may require onsite attendance 5 days per week as will be indicated in the job posting.

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://bit.ly/faire-form).

For information about the type of personal data Faire collects from applicants, as well as your choices regarding the data collected about you, please visit Faire’s Privacy Notice (https://www.faire.com/privacy).