​​​​

Our Client -

Company Description

Our client, BlueCrew Founded in 2015, acquired by InterActive Corp (IAC) in 2018, and recognized by Fast Company as the 8th most innovative workplace company of 2020, Our client is disrupting traditional hourly staffing (a $130 billion addressable market, almost exclusively offline) by pioneering “Gig 2.0”. 

Our hourly workers - we call them Crew Members - are our client's lifeblood. We employ thousands of W-2 workers who are dependable, looking for flexibility, and ready to accept short or long term job proposals, which they are intelligently matched with by our Elastic Hourly Workforce (EHW) platform. Our Client's EHW platform combines multiple products and services into an end-to-end, simple-to-use app/web solution for our Crew Members to manage their work lives, and for our workplace customers to manage their hourly workforce.

Our workplace customers are challenged with variable demand; longer term, more predictable variability such as seasonal and cyclical; and less predictable, shorter term variability like absenteeism and large unexpected customer orders. This variability in demand creates complex challenges to effectively and efficiently manage variability in hourly labor which until our client, has been left unsolved.

Job Description:

This high-impact analytical leader will be the company's "go-to" data person and will be the founding member of the data team. They will build architectures and pipelines to allow for self-service reporting, build Machine Learning models and help our client build new revenue sources. This leader will also advise the company on setting up experimentation frameworks and data analysis. 

Job Requirements:

The ideal candidate should be able to have following: 

• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases is required
• Analyze and organize raw data
• Build data systems and pipelines
• Conduct complex data analysis and report on results
• Prepare data for prescriptive and predictive modeling
• Combine raw information from different sources
• Explore ways to enhance data quality and reliability
• Identify opportunities for data acquisition
• Develop analytical tools and programs
• Some familiarity with scripting languages