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When JetBlue first took flight in February 2000, our founding goal was to bring humanity back to air travel, and over two decades later, we still put our customers, crewmembers and communities at the center of everything we do.
Before we even had aircraft to fly, our founders selected five values to guide us, which are safety, caring, integrity, passion and fun. These core values shape our culture and empower our 23,000 crewmembers to deliver a meaningful JetBlue experience to more than 40 million customers that fly with us each year to more than 100 cities across the United States, Latin America, Caribbean, Canada and Europe.
We’re proud to be New York's Hometown Airline®, and a leading carrier in Boston, Fort Lauderdale - Hollywood, Los Angeles, Orlando, and San Juan.
Data Scientist
JetBlue
On-site
New York, NY, United States
Full-time
$91,000 -
$129,000
About JetBlue
About the Role
The Data Science & Analytics team at JetBlue is an integral part of the IT Data organization which reports directly to the Chief Digital & Technology Officer due to the strategic importance of Data at JetBlue. The Data Science & Analytics team consists of Operations Data Science (ODS), Commercial Data Science (CDS), Artificial Intelligence (AI) & Machine Learning (ML) engineering, and Business Intelligence teams operating in a center-of-excellence model reporting to the Senior Manager, Data Science & Analytics. The teams develop advanced Data products and insights for all cross-functional teams at JetBlue including up/cross-skilling the internal analyst community.
The Data Scientist applies machine learning and statistical techniques to help solve JetBlue’s most complex commercial and operational challenges. The Data Scientist will be responsible for Exploratory Data Analysis (EDA), feature engineering, feature selection, real-time streaming pipeline engineering, online/offline feature store curation, iterating various modeling approaches, evaluating error metrics, deploying Machine Learning models to the cloud, creating compelling visualizations and communicating findings effectively to large audiences. The Data Scientist reports to the Manager, Data Science.
The Data Scientist applies machine learning and statistical techniques to help solve JetBlue’s most complex commercial and operational challenges. The Data Scientist will be responsible for Exploratory Data Analysis (EDA), feature engineering, feature selection, real-time streaming pipeline engineering, online/offline feature store curation, iterating various modeling approaches, evaluating error metrics, deploying Machine Learning models to the cloud, creating compelling visualizations and communicating findings effectively to large audiences. The Data Scientist reports to the Manager, Data Science.
Qualifications
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 relevant work experience.
Three (3) years of relevant industry experience.
Proficiency in Python, SQL, git and common data science and machine learning libraries.
Experience building machine learning models.
Able to write production quality code and be familiar with software engineering best practices, including testing and version control.
Ability to communicate their findings to both technical and non-technical audience.
Ability to successfully complete technical interviews and take-home test in areas of statistics, machine learning, SQL, Python, PySpark, optimization and MLOps.
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.
Preferred Experience And Qualifications
Advanced degree in Computer Science or a quantitative discipline.
Four (4) years of relevant industry experience.
Experience applying various Machine Learning techniques such as: Time Series Forecasting, Recommendation Systems, A/B Testing, Dynamic Pricing, Logistics Optimization, Churn Analysis, Segmentation Analysis, Natural Language Processing, Deep Learning and Reinforcement Machine Learning.
Experience using Databricks, PySpark / Spark, Azure Cloud, Kubernetes, Docker, PyTorch, Keras, Tensorflow.
Three (3) years of relevant industry experience.
Proficiency in Python, SQL, git and common data science and machine learning libraries.
Experience building machine learning models.
Able to write production quality code and be familiar with software engineering best practices, including testing and version control.
Ability to communicate their findings to both technical and non-technical audience.
Ability to successfully complete technical interviews and take-home test in areas of statistics, machine learning, SQL, Python, PySpark, optimization and MLOps.
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.
Preferred Experience And Qualifications
Advanced degree in Computer Science or a quantitative discipline.
Four (4) years of relevant industry experience.
Experience applying various Machine Learning techniques such as: Time Series Forecasting, Recommendation Systems, A/B Testing, Dynamic Pricing, Logistics Optimization, Churn Analysis, Segmentation Analysis, Natural Language Processing, Deep Learning and Reinforcement Machine Learning.
Experience using Databricks, PySpark / Spark, Azure Cloud, Kubernetes, Docker, PyTorch, Keras, Tensorflow.
Responsibilities
Collaborate with teams across the business to translate their needs or challenges into machine learning or statistical problems.
Collaborate with business, engineering, infrastructure and data science teams to translate their needs or challenges into production-grade Artificial Intelligence (AI) and Machine Learning (ML) deployment architectures for batch, real-time streaming and edge deployments.
Integrate Artificial Intelligence & Machine Learning products through common libraries, robust data and Continuous Integration/Continuous Delivery (CI/CD) pipelines, deployment standards and documentation.
Support the development of data products through exploratory data analysis, feature engineering and model building.
Effectively communicate experiments, models and analytics outputs with partners.
Other duties as assigned.
Collaborate with business, engineering, infrastructure and data science teams to translate their needs or challenges into production-grade Artificial Intelligence (AI) and Machine Learning (ML) deployment architectures for batch, real-time streaming and edge deployments.
Integrate Artificial Intelligence & Machine Learning products through common libraries, robust data and Continuous Integration/Continuous Delivery (CI/CD) pipelines, deployment standards and documentation.
Support the development of data products through exploratory data analysis, feature engineering and model building.
Effectively communicate experiments, models and analytics outputs with partners.
Other duties as assigned.
Benefits
Base pay is one component of JetBlue’s total compensation package, which may also include access to healthcare benefits, a 401(k) plan and company match, crewmember stock purchase plan, short-term and long-term disability coverage, basic life insurance, free space available travel on JetBlue, and more.
