Data Scientist, Square for Retail
Vancouver, Canada
3d ago

Job Description

From the cozy local wine store to the trendy sneaker pop-up, the Retail team at Square is equipping retail sellers with simple solutions to complex problems - like predictive analytics and fluid, omni-channel capabilities to meet customers wherever they are.

Square’s mission is economic empowerment, and Data Scientists support this by using data to understand and empathize with our customers, thereby enabling us to build a remarkable product experience.

You and your fellow data science & analytics teammates on the Retail Analytics team are embedded within product and marketing sub-teams ( squads ), leveraging data engineering, analytics, statistics, and machine learning to empower data-driven decision making in the full life cycle of product development.

You will :

Partner with the product, design, and marketing stakeholders to identify, prioritize, and answer the most important questions where analytics can have a material impact

Apply a diverse set of tactics such as statistics, quantitative reasoning, and machine learning; discerning where simple analytics solutions (e.

g. a quick heuristic or visualization) are preferable to complex solutions (e.g. machine learning)

Contribute to the data strategy of product engineering, influencing engineers to make well-informed architecture and design decisions that affect data at Square

Provide comprehensive day-to-day analytics support to partner teams, developing tools and resources to empower data access and self-service so your advanced expertise can be leveraged where it is most impactful

You have :

2+ years of analytics experience

Fluency in SQL, with experience exploring and understanding large, complex datasets & data systems

Experience working with technical and non-technical partners, such as product managers and product marketing managers

Experience with statistical and machine-learning techniques to solve practical business problems such as hypothesis testing, clustering user archetypes, or predicting churn

Very strong communication skills : ability to clearly communicate complex results to technical and non-technical audiences in verbal, visual, and written media

Experience maintaining a backlog and performing independently

Even better :

Experience with a BI tool such as Looker or Tableau

Experience with data warehouse design, development and best practices

A degree in Mathematics, Statistics, Computer Science, Physical Sciences, Economics, or a related technical field

Technologies we use and teach :

Airflow (ETL)

Looker, Amplitude, Tableau

Python (pandas, scikit-learn, etc.)

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