Are you a Data Scientist who is passionate about using Machine Learning to create and deliver value using data? Poshmark is looking for a Lead Data Scientist who can lead Data Science initiatives.
As a market leader in Social Commerce, Poshmark faces a 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 and help solve some of the most challenging problems in social commerce like pricing, search ranking, product and people recommendation, fraud prevention and many more.
Help develop vision, business case, modeling spec and operational project plans for end-to-end ML solution
Lead the development of data science / ML models for high business impact opportunities across all business areas
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, continuous improvement
Train, mentor and guide junior data scientists in the team
Partner with product, data engineering and ML engineering teams to ensure seamless productionzation of developed algorithm and management of full model cycle
Develop and 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
Lead the development of standard building blocks for usage across multiple ML algorithms
Qualifications and skills
5+ years of hands-on experience in building scalable Machine Learning based solutions in a Big Data environment.
Fluency in all steps of data science solution development cycle from business problem identification to business value delivery
Ability to do insightful data analysis both pre and post ML model development to estimate impact, establish feasibility, understand model performance, validate hypothesis and answer questions from stakeholders
Expert level hands-on / applied knowledge of key machine learning algorithms
Ability to choose a technique based on the problem and the data, ability to debug and reason about why a model may not be working as expected
Expert hands-on knowledge of Python and data science / ML packages
Hands-on knowledge of SQL with the ability to write readable and efficient queries for complex data crunching
Hands-on experience in using Spark (Scala or Pyspark) to process data at large scale
Hands-on experience in using MS Excel to do quick exploratory data analysis using basic functions, pivot tables and charts
Experience partnering with ML engineering teams in deploying ML models to production
Experience in training and mentoring junior data scientists
Strong business / product sense and excellent verbal and written communication skills for a variety of audiences : executive teams, product managers, engineers, and business leaders
Excellent problem solving skills coupled with a passion to solve challenging problems using data science / ML with focus on delivering business value
MS in a relevant quantitative field such as Computer Science, Statistics, Math is a plus