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Machine Learning Scientist

šŸš€ Whatnot Whatnot is a livestream shopping platform and marketplace backed by Andreessen Horowitz, Y Combinator, and CapitalG. Weā€™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... Weā€™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, weā€™re growingā€“fast. Whatnot has been the fastest growing marketplace in the US over the past two years and has been named Glassdoor's best place to work in the small and medium business category. Weā€™re hiring forward-thinking problem solvers across all functional areas. šŸ’» Role We are looking for intellectually curious, entrepreneurial individuals to become foundational members of our Core Machine Learning team. Bringing to bear a mixture of model development and software engineering skills, you will design, develop, and deploy modes and scaled solutions to solve 0 to 1 problems across a wide variety of product surfaces. The Core Machine Learning team architects design patterns while actively contributing to initiatives spanning search, recommendation, growth, trust and safety, and fraud, to name a few. The ideal candidate is excited by the prospect of end to end execution of projects and is willing and able to wear multiple hatsā€“no two days are exactly the same at a fast growing startup! What you'll do: ā€¢ Develop and deploy new production machine learning algorithms and systems that enrich the buyer and seller experience. ā€¢ Build and help set direction across the entire machine learning development process to implement production algorithms, including exploratory data analysis, data modeling, feature engineering, model training, testing, deployment, and monitoring. ā€¢ Contribute across the data science and machine learning development stack: ideation, opportunity sizing, prototyping, load testing, deployment, and monitoring. ā€¢ Drive initiatives across multiple product areas and communicate findings with leadership and product teams using dashboards, notebooks, and/or documents where appropriate. ā€¢ Design and implement end-to-end data pipelines and systems that support MLOps and critical business processes. ā€¢ Deep dive into mission-critical problems unique to Whatnotā€™s livestream auction ecosystem and design bespoke algorithmic solutions. šŸ‘‹ You Curious about who thrives at Whatnot? Weā€™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 4+ years of professional experience developing machine learning systems and algorithms, plus: ā€¢ Bachelorā€™s degree in Computer Science, Statistics, Applied Mathematics, Economics, a related technical field, or equivalent work experience. ā€¢ 1+ years of software or machine learning engineering experience building for consumer-scale loads. ā€¢ Industry experience with a track record of applying the scientific methods to solve real-world problems on consumer scale data. ā€¢ Experience leading work to develop and deploy machine learning- and data-based solutions in production. ā€¢ Extensive experience with Python and SQL for data science, machine learning, and software development e.g. PyTorch, LightGBM, FastAPI ā€¢ Ability to work autonomously and lead initiatives across multiple product areas and communicate findings with leadership and product teams. ā€¢ Comfortability with data warehouses and transformation tools such as Snowflake, dbt, Dagster. ā€¢ Proficiency and experience in applied statistics and machine learning fields e.g. Experimentation and Causal Analysis, Recommendations, Fraud & Anomaly Detection, Natural Language Processing. ā€¢ Professionalism around collaborating in a remote working environment and well tested reproducible work. ā€¢ Above average documentation and communication skills. šŸ’°Compensation For US-based applicants: $180,000 - $285,000/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. šŸŽ Benefits ā€¢ Flexible Time off Policy and Company-wide Holidays (including a spring and winter break) ā€¢ Health Insurance options including Medical, Dental, Vision ā€¢ Work From Home Support ā€¢ $1,000 home office setup allowance ā€¢ $150 monthly allowance for cell phone and internet ā€¢ Care benefits ā€¢ $450 monthly allowance on food ā€¢ $500 monthly allowance for wellness ā€¢ $5,000 annual allowance towards Childcare ā€¢ $20,000 lifetime benefit for family planning, such as adoption or fertility expenses ā€¢ Retirement; 401k offering for Traditional and Roth accounts in the US (employer match up to 4% of base salary) and Pension plans internationally ā€¢ Parental Leave ā€¢ 16 weeks of paid parental leave + one month gradual return to work *company leave allowances run concurrently with country leave requirements which take precedence. šŸ’› 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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CEO of Whatnot
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Grant LaFontaine
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Whatnot is a livestream shopping platform and marketplace backed by Andreessen Horowitz, Y Combinator, and CapitalG.

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Full-time, remote
DATE POSTED
June 30, 2024

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