Manager Technology Data Science TechOps

JetBlue Airways Corporation•New York, NY

1d•$118,800 - $177,100•Hybrid

About The Position

The Manager, IT Data Science leads a team of data scientists who will design experiments and develop machine learning models to address the most complex data problems at JetBlue. The individual must be an experienced data scientist with broad knowledge of machine learning and statistical techniques who writes and can review production Python code. The Manager will establish best practices for data science workflows and knows how to create an environment and team culture that enables data scientists to perform at their best. The Manager works in an entrepreneurial role, building the team, data products, and vision of data science at JetBlue from the ground up. JetBlue’s Data Team is fast-growing and has been tasked at the senior-most level to solve some of the highest-impact challenges faced by the business. The Manager reports to the General Manager, IT Data Science (Data Team), building a sense of trust and partnership to create a comfortable and productive workplace, while taking ownership over duties in a high-energy, passionate, and face-paced team environment.

Requirements

Bachelor’s degree in Computer Science or a quantitative discipline; OR demonstrated capability to perform job responsibilities with a combination of a High School Diploma/GED and at least four (4) years of previous related work experience
Five (5) years of relevant industry experience, including technical management of product roadmaps and/or people management of data science teams
Expert proficiency in Python, SQL, git and common data science and machine learning libraries
Experience deploying machine learning models in production in a company setting
Excellent verbal and written communication skills, with experience working directly with senior management
Available for overnight travel (10%)
Must pass a pre-employment drug test
Must be legally eligible to work in the country in which the position is located

Nice To Haves

Experience applying several data science techniques: Forecasting, Recommendation Systems, Logistics Optimization, Churn Analysis, Segmentation Analysis, Deep Learning
Experience with Databricks, PySpark / Spark, Snowflake, dbt, Azure Cloud

Responsibilities

Collaborate with product, engineering, operations, finance, and marketing teams to translate their needs or challenges into machine learning or statistical problems
Establish an operating model, standard project structure, and requirements for the data science team
Recruit and lead a motivated team of data scientists
Oversee and guide the development of data products, providing direction on the appropriate models to use and the correct engineering approach
Effectively communicate experiments, models and analytics outputs with partners and executives
Take a significant role in the development of crewmembers to support their engagement, growth, and goal achievement
Other duties as assigned