Machine Learning Scientist

San Francisco, CA, Los Angeles, CA, New York City, Phoenix, AZ, Seattle, WA, Denver, CO, Toronto, ON

🚀 Whatnot

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, and as a remote-first team, we operate out of hubs within the US, Canada, UK, Ireland, and Germany today.

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. 

💻 Role

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.

👋 You

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 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.

💰Compensation

For US-based applicants: $178,000 - $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.

🎁 Benefits

  • Flexible Time off Policy and Company-wide Holidays (including a spring and winter break)
  • Health Insurance options including Medical, Dental, Vision
  • Work From Home Support
    • $1,000 home office setup allowance
    • $150 monthly allowance for cell phone and internet
  • Care benefits
    • $450 monthly allowance on food
    • $500 monthly allowance for wellness
    • $5,000 annual allowance towards Childcare
    • $20,000 lifetime benefit for family planning, such as adoption or fertility expenses
  • Retirement; 401k offering for Traditional and Roth accounts in the US (employer match up to 4% of base salary) and Pension plans internationally
  • Parental Leave
    • 16 weeks of paid parental leave + one month gradual return to work *company leave allowances run concurrently with country leave requirements which take precedence.

💛 EOE

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.

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Tags: Computer Science Computer Vision Dagster Data analysis Data pipelines dbt Docker E-commerce EDA Engineering FastAPI Feature engineering Flask Jupyter LightGBM Machine Learning Mathematics MLOps Model training NumPy Pandas Pipelines Prototyping Python PyTorch Scikit-learn SciPy Snowflake SQL Statistics Testing

Perks/benefits: 401(k) matching Career development Cell phone stipend Equity Fertility benefits Flex hours Flex vacation Health care Home office stipend Insurance Medical leave Parental leave Startup environment Wellness

Region: North America
Countries: Canada United States
Job stats:  45  17  0

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