Logistic jobs in United Arab Emirates

About Faire

Faire is an online wholesale marketplace built on the belief that the future is local — independent retailers around the globe are doing more revenue than Walmart and Amazon combined, but individually, they are small compared to these massive entities. 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 that small businesses everywhere can compete with these big box and e-commerce giants.

By supporting the growth of independent businesses, Faire is driving positive economic impact in local communities, globally. 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 (ML) 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 Lifetime Value (LTV) predictions. Our ultimate goal is to empower local retail businesses with the tools they need to succeed.

As a Data Scientist on the Retailer team, you'll tackle a diverse set of challenges, such as optimizing logistics and freight costs and calculating optimal credit limits. You'll also contribute to growing Faire’s retailer base by enhancing Search Engine Optimization, personalizing landing pages for new retailers, and predicting retailer lifetime value. You'll collaborate closely with other data scientists, engineers, and product managers to drive projects that unlock value from our unique, rich, and rapidly growing two-sided marketplace data.

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

What you’ll do

• Shipping cost optimization: Build ML models that provide accurate shipping cost estimates. Engineer new features to improve model performance. These models may use live carrier information and be both performant and explainable.
• Underwriting: Improve Faire’s Net terms portfolio by evaluating creditworthiness of retailers on Faire’s platform. Use predictive modeling to dynamically assign credit terms limits that minimize default risk and maximize growth.
• Retailer Growth & Lifecycle: Build models to automatically generate landing pages and content to target search engine demand. Use natural language processing to understand search engine keyword intent and match to relevant internal content. Build ML models to generate intelligence about retailers to power personalization. Predict retailer lifetime values to optimize retailer acquisition spend.

Qualifications

• An advanced degree (MS or PhD) in a relevant discipline such as statistics, economics, econometrics, mathematics, computer science, operations research, etc.
• Strong machine learning skills and 3+ years of experience productionizing machine learning models (Sklearn, XGBoost, or Deep Learning)
• Strong programming skills (Python, Java, Kotlin, C++)
• Knowledge of statistical techniques such as experimentation and causal inference
• SQL or other database querying experience preferred
• An excitement and willingness to learn new tools and techniques

Salary Range

Canada: the pay range for this role is $168,000 to $231,000 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.

This role will be in-office on a hybrid schedule - Faire employees will be expected to go into the office 2 days per week on Tuesdays and Thursdays, effective the week of January 13, 2025. Additionally, in-office roles will have the flexibility to work remotely up to 4 weeks per year.

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. 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.