Recherche d'emploi > Toronto, ON > Data scientist

Staff Data Scientist - Marketplace Quality

Faire
Toronto, ON
167K $-230K $ / an
Temps plein

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 data scientists and machine learning engineers specialize in developing algorithmic solutions for notification and recommender systems, advertising attribution, and LTV predictions.

Our ultimate goal is to empower local retail businesses with the tools they need to succeed.

At Faire, the Data Science team is responsible for creating and maintaining a diverse range of algorithms and models that power our marketplace.

We are dedicated to building machine learning models that help our customers thrive.

As the Marketplace Quality lead within the Brand Data Science team, you will be responsible for improving the quality of retailers’ experiences with products and brands on Faire, particularly by reducing egregious issues, such as counterfeit products, fulfillment delays, damaged and missing items, and poor quality products.

You will develop data science models to detect and act on issues. This will involve issue detection from unstructured data, human-in-the-loop targeting, causal inference, and lever optimization.

You will independently drive data science vision, strategy, and execution and be the data science lead within the cross-functional Marketplace Quality pod, thinking end-to-end about the problem.

Our team already includes experienced Data Scientists from Uber, Airbnb, Square, Facebook, and Pinterest. Faire will soon be known as a top destination for data scientists and machine learning engineers, and you will help take us there!

What you’ll do

Drive data science vision, strategy, and execution on Marketplace Quality, reducing the bad experiences that retailers encounter in the marketplace (e.

g. counterfeits, late shipment, damaged and missing items, poor product quality)

  • Act as a lead on the cross-functional Marketplace Quality pod, thinking end-to-end about brand and retailer experiences, ops processes, policy enforcement, etc.
  • Use deep learning techniques to match products across platforms, detect issues from image and text data, and summarize reviews
  • Use causal inference methods to estimate the long term effects of quality issues and optimize the tradeoff between reducing issues and near-term growth
  • Optimize levers such as downranking and Top Shop status to drive visibility away from low quality and toward high quality products and brands
  • Develop human-in-the-loop machine learning systems for detecting issues and targeting actions
  • Solve challenging problems related to a two-sided marketplace

Qualifications

  • 5+ years of industry experience using machine learning to solve real-world problems
  • Experience with relevant business problems (e-commerce, marketplaces, or logistics)
  • Experience with relevant technical methods (human-in-the-loop machine learning, causal inference, and / or deep learning)
  • 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
  • Strong communication skills and the ability to work in a highly cross-functional team

Great to Haves :

  • Highly recommended : Master’s or PhD in Computer Science, Statistics, or related STEM fields
  • Previous experience in marketplace quality in a two-sided e-commerce platform
  • Previous experience in deep learning or language models

Salary Range

Canada* : the pay range for this role is $167,000 to $230,000 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.

Faire’s flexible work model aims to meet the needs of our diverse employee community by making work more flexible, connected, and inclusive.

Depending on the role and needs of the team, Faire employees have the flexibility to choose how they work whether that’s mainly in the office, remotely, or a mix of both.

Roles that list only a country in the location are eligible for fully remote work in that country or in- office work at a Faire office in that country, provided employees are located in the registered country / province / state.

Roles with only a city location are eligible for in-office or hybrid office work in that city. Our talent team will work with candidates to determine what locations and roles are eligible for each option.

Applications for this position will be accepted for a minimum of 30 days from the posting date.

Why you’ll love working at Faire

We are entrepreneurs : Faire is being built for entrepreneurs, by entrepreneurs. We believe entrepreneurship is a calling and our mission is to empower entrepreneurs to chase their dreams.

Every member of our team is taking part in the founding process.

  • We are using technology and data to level the playing field : We are leveraging the power of product innovation and machine learning to connect brands and boutiques from all over the world, building a growing community of more than 350,000 small business owners.
  • We build products our customers love : Everything we do is ultimately in the service of helping our customers grow their business because our goal is to grow the pie - not steal a piece from it.

Running a small business is hard work, but using Faire makes it easy.

We are curious and resourceful : Inquisitive by default, we explore every possibility, test every assumption, and develop creative solutions to the challenges at hand.

We lead with curiosity and data in our decision making, and reason from a first principles mentality.

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.

To request reasonable accommodation, please fill out our (https : / / bit.ly / faire-form)

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