About the Role
Poshmark is seeking a passionate Data Science Manager who can independently lead and deliver Data Science initiatives. As a market leader in Social Commerce, Poshmark offers a unique opportunity to leverage massive multi-platform social and commerce data to shape social commerce and create value for its users. With over 500 million events per day and more than 40 terabytes of exponentially growing data, Poshmark presents a unique opportunity to innovate cutting-edge data science and machine learning products. This role will involve working on Data Science initiatives across product, marketing, operations, and community, helping to solve challenging problems in social commerce such as pricing, search ranking, product and people recommendation, feed ranking, and fraud prevention.
Key Responsibilities
- Develop business case, modeling spec, and operational project plans for end-to-end ML solutions.
- In partnership with data leaders and the ML engineering team, lead the development of data science/machine learning models for high business impact opportunities across all business areas.
- Independently own project and stakeholder management for short-term and long-term data science/ML projects.
- Manage, mentor, and empower a team of data scientists.
- Work on all stages of a data science/ML project: exploration and conceptualization, POC (proof of concept), data preparation, model development and testing, deployment, monitoring and debugging, and continuous improvement.
- Proactively partner with product, data engineering, and ML engineering teams to ensure seamless productionization of developed algorithms and management of the full model cycle for business application.
- Develop and follow best practices for developing, managing, maintaining, and documenting machine learning models and all related work.
- Define and abstract standard building blocks for usage across multiple ML algorithms.
- Innovate new solutions for unique challenges facing Poshmark, including publishing academic papers, white papers, blog posts, and presenting at leading conferences.
Qualifications and Skills
- 7+ years of experience in delivering scalable Machine Learning based solutions in a Big Data environment.
- 2+ years of experience in people management.
- Fluency in all steps of the data science solution development cycle from business problem identification to business value delivery.
- Ability to design insightful data analysis both pre and post ML model development to estimate impact, establish feasibility, understand model performance, validate hypotheses, and answer questions from stakeholders.
- Excellent project and stakeholder management skills.
- Expert-level knowledge of Python, SQL, and Spark (Scala or Pyspark) and key machine learning algorithms.
- Extensive experience partnering with ML engineering teams in deploying ML models to production.
- Strong business/product sense and excellent verbal and written communication skills for a variety of audiences: executive teams, product managers, engineers, and business leaders.
- PhD or MS in a relevant quantitative field such as Statistics, Math, or Computer Science is a huge plus.