Whatnot is a livestream shopping platform and marketplace backed by Andreessen Horowitz, Y Combinator, and CapitalG. We’re building the future of ecommerce, bringing together community, shopping and entertainment. We are committed to our values, whether working remotely or from one of our offices. We are building a team that has experience from top tech, retail and payments platforms in the world.
We’re innovating in the fast-paced world of live auctions in categories including sports, fashion, video games, and streetwear. The platform couples rigorous seller vetting with a focus on community to create a welcoming space for buyers and sellers to share their passions with others.
And, we’re growing. Whatnot has been the fastest growing marketplace in the US over the past two years and we’re hiring forward-thinking problem solvers across all functional areas.
📈 Opportunity Size
Retail disruption is one of the largest opportunities in the startup space today. Livestream shopping is taking off around the world – a $300B GMV market in China that’s grown 100% YoY. Whatnot is bringing it to the world through a community-first approach, starting in the U.S. where retail is a $5T market opportunity!
We are looking for intellectually curious, highly motivated individuals to be foundational members of our Machine Learning and Data Platform team. You will partner across the company and use data to design scalable solutions based on a deep understanding of critical business goals. The ideal candidate will leverage data analysis, statistics and machine learning to lead initiatives end to end, including data & machine learning engineering.
What you'll do:
- Build and help set direction across the entire machine learning development process to implement machine learning algorithms in production, including exploratory data analysis, data modeling, feature engineering, model training and tuning, testing, deployment, and monitoring.
- Partner closely across the business to identify improvements and influence decisions using data science methodologies and tools.
- Develop new production machine learning algorithms and systems that enrich the app experience with machine learning-powered experiences.
- Contribute across the data science and machine learning development stack: idea development, opportunity sizing, prototyping, testing, and deployment.
- Design and implement end-to-end data pipelines and data systems that support MLOps and business processes.
- Build high quality communication devices such as dashboards, notebooks, documents, presentations to convey insights across a broad audience.
- Define and advance standard methodologies within an experiment-driven culture.
- Bachelor’s degree in Computer Science, a related field, or equivalent work experience.
Curious about who thrives at Whatnot? We’ve found that low ego, a growth mindset, and leaning into action and high impact goes a long way here.
As our next Senior Machine Learning Scientist you should have 5+ years of experience, plus:
- Bachelor’s degree in Computer Science, Statistics, Mathematics, Software Engineering or related technical field., or equivalent work experience.
- Industry experience with a track record of applying scientific methods to solve real-world problems on consumer scale data.
- Experience leading work to develop and deploy machine learning- and data-based solutions in production.
- Extensive experience with Python and SQL for data science, machine learning, and software development e.g. numpy, scipy, pandas, scikit-learn, PyTorch, LightGBM, Flask, FastAPI, Docker, Jupyter.
- Ability to work autonomously and lead initiatives across multiple product areas and communicate findings with leadership and product teams.
- Comfortability with data warehouses and transformation tools such as Snowflake, dbt, Dagster.
- Proficiency and experience in applied statistics and machine learning fields e.g. Experimentation and Causal Analysis, Recommendations, Fraud & Anomaly Detection, Natural Language, Computer Vision.
- Firm grasp of visualization tools, interactive and self-serving, such as dashboards and notebooks.
- Professionalism around collaborating in a remote working environment and well tested reproducible work.
- Above average documentation and communication skills.
For US-based applicants: $153,000 - $235,000/year + benefits + stock options
The salary range may be inclusive of several levels that would be applicable to the position. Final salary will be based on a number of factors including, level, relevant prior experience, skills and expertise. This range is only inclusive of base salary, not benefits (more details below) or equity in the form of stock options.
- Competitive base salary and stock options
- Unlimited Vacation Policy and Company-wide Holidays (including a spring and winter break)
- Health Insurance options including Medical, Dental, Vision, Life, Short term disability & Long term Disability
- Whatnot covers 99% of employee premium costs, and 75% of dependent care premiums for Medical
- Dental and Vision sponsored 100% by Whatnot for employees and dependents
- Work From Home Support
- Laptop provided by Whatnot and home office setup allowance
- $450 work-from-anywhere quarterly allowance for cell phone and internet
- Care benefits
- $1,350 quarterly allowance on food
- $1,500 quarterly allowance for wellness
- 16 weeks Paid Parental Leave and gradual return to work
- $5,000 annual allowance towards Childcare
- $20,000 lifetime benefit for family planning, such as adoption or fertility expenses
- Professional Development
- $2,000 annual benefit to invest in your professional development
- 401k offering for Traditional and Roth accounts provided by Betterment
- Employer matching contributions of 100% of up to 4% of contributions on base salary
Whatnot is proud to be an Equal Opportunity Employer. We value diversity, and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, parental status, disability status, or any other status protected by local law. We believe that our work is better and our company culture is improved when we encourage, support, and respect the different skills and experiences represented within our workforce.