Overview:

Do you have a passion for solving impactful problems using data science? Gopuff is building solutions to dramatically change the way people purchase their daily goods. We provide the modern-day solution to meet customers immediate everyday needs with products ranging from snacks and ice cream to household goods and beer, at the click of a button.

Our business is built on a backbone of technology, which generates high-quality data from shopping to facilities management to order fulfillment.

As a Data Scientist on the Gopuff consumer science team, you’ll have the opportunity to work on a wide variety of high impact projects related to Search and Recommendations. You’ll have ownership from prototype to productionalization and the across functional support to launch 0-1 systems. You’ll refine our existing systems in retrieval, ranking and query understanding so that we can show the perfect products to enhance users’ discovery experience, and youll be able to build aspects of search from the bottom up. You’ll make a huge impact on the future success of Gopuff.

This is a remote position.

You Will:

Build and enhance machine learning, statistical and causal models for product search, ranking and recommendation that support various business goals
Work closely with product and engineering managers to develop and deploy solutions with cross-functional support
Educate our business and engineering partners across the organization on data science concepts (e.g., statistics, machine learning)
Build models that support real-time events
Present work to business and engineering leadership
Identify gaps in existing data, create data product specs, and work with Engineering teams to implement enhanced data tracking
Partner with Analytics team members and other functions to share insights and best practices, ensuring consistency of data-driven decision-making throughout the org
Commit to automation and productionalized solutions whenever possible
Provide mentorship to less experienced data scientists

You Have:

MS or PhD in statistics, mathematics, analytics, computer science or another quantitative field AND 3+ years of experience as a data scientist in eCommerce or Logistics
Or, 8+ years of experience as a data scientist in eCommerce or Logistics
Hands-on experience in building ranking and recommendation models in production environments
Experience applying descriptive statistics, machine learning, predictive modeling, and visualization techniques to solve challenging business problems

Expert knowledge in:

Statistical and machine learning techniques
Data Science libraries in a programming or scripting languageModel deployment
Machine learning workflows

Proficient in:

Python + related ML libraries and frameworks (Ex: PyTorch)
Proficient in SQL and working with large datasets.
Experience with cloud platforms (e.g., AWS, GCP, Azure) and model development and deployment technologies (e.g., Databricks).
Excellent communication and presentation skills (to both technical and business audiences)

Compensation

Gopuff pays employees based on market pricing and pay may vary depending on your location. The salary range below reflects what we’d reasonably expect to pay candidates. A candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. These ranges may be modified in the future. For additional information on this role’s compensation package, please reach out to the designated recruiter for this role.
Remote US Range: $160,000 - 260,000

At Gopuff, we know that life can be unpredictable. Sometimes you forget the milk at the store, run out of pet food for Fido, or just really need ice cream at 11 pm. We get it—stuff happens. But that’s where we come in, delivering all your wants and needs in just minutes.

And now, we’re assembling a team of motivated people to help us drive forward that vision to bring a new age of convenience and predictability to an unpredictable world.

Like what you’re hearing? Then join us on Team Blue.

Gopuff is an equal employment opportunity employer, committed to an inclusive workplace where we do not discriminate on the basis of race, sex, gender, national origin, religion, sexual orientation, gender identity, marital or familial status, age, ancestry, disability, genetic information, or any other characteristic protected by applicable laws. We believe in diversity and encourage any qualified individual to apply.