About the Role
Are you a Data Scientist who is passionate about using Machine Learning to create and deliver value from Data? Poshmark is looking for a Sr Data Scientist who can independently drive Data Science initiatives. As a market leader in Social Commerce, Poshmark faces unique opportunity to utilize our massive multi-platform social and commerce data to shape social commerce and create value for our users. With 400+ MM events per day and 30+ terabytes of exponentially growing data, Poshmark presents a unique opportunity to innovate cutting edge data science products. This person will work on all Data Science initiatives across product, marketing, Posh markets, operations and community.
Key Responsibilities
- Help develop vision, business case, modeling spec and operational project plans for end-to-end ML solution
- In partnership with data leaders and ML engineering team, lead hands-on development of data science/machine learning models for high business impact opportunities across all business areas
- Partner with product, data engineering and ML engineering teams to ensure seamless productionzation of developed algorithm and management of full model cycle for business application
- Follow best practices for developing, managing, maintaining and documenting machine learning models and all related work
- Develop a deep understanding of different business functions and core KPI to ensure that the data science solution fits the business need
- Define and abstract standard building blocks for usage across multiple ML algorithms. Lead productization, development and maintenance of these. E.g. feature library, model testing automation, model validation and recommendation automation
- Innovate new solutions for unique challenges facing Poshmark. Publish academic papers, white papers, blog posts and present in leading conferences.
Qualifications
- 4+ years of hands-on experience in building scalable ML algorithms based data solutions in Big Data environment.
- Fluency in all steps of data science solution development cycle from business problem identification to business value delivery
- Expert level hands-on theoretical and applied knowledge of key machine learning algorithms, relevant programming languages and relevant open-source technologies and packaged ML software.
- Experience partnering with ML engineering teams in implementing ML models
- Strong business acumen and excellent verbal and written communication skills for a variety of audiences: executive teams, product managers, engineers, and business leaders
- Passionate to solve difficult problems using data science/ML with focus on delivering business value
- PhD or MS in a relevant quantitative field such as Statistics, Math, Computer Science is a huge plus