Sr. Data Scientist
Title : Sr. Data Scientist
Remote work
Top Skills:
Airline Revenue Management experience is a must
Google Cloud (GCP) that is the preference but other cloud experience will work.
Programming- Python and C++
Data: PySpark
Experience with Rally and JIRA is good.
Description
The Data Science Engineer applies expert level statistical analysis, data modeling, and predictive analysis on strategic and operational problems in airline industry. As a key member of the Operations Research team, you will leverage your statistical and business expertise to translate business questions into data analysis and models, define suitable KPIs, and graphically present results to a wide range of audiences including internal and external clients, sales, and development team. In addition, you will source data from multiple different data sources, write high-quality data manipulation scripts in R, Python, Perl, bash, etc., develop and ap-ply data mining and machine learning algorithms for advanced analysis and prediction. You will also utilize your strong communication skills to work with developers to support product development cycles and decision makers who need empirical data to promote sales and growth.
Responsibilities
Understanding of airline distribution, pricing, revenue management, NDC and Offer/Order Management concepts.
Work with subject matter experts from airlines to identify opportunities for leveraging data to deliver in-sights and actionable prediction of customer behavior and operations performance.
Assess the effectiveness and accuracy of new data sources, data gathering and forecasting techniques.
Develop custom data models and algorithms to apply to data sets and run proof of concept studies.
Leverage existing Statistical and Machine Learning tools to enhance in-house algorithms.
Collaborate with software engineers to implement and test production quality code for forecasting and data analytics models.
Develop processes and tools to monitor and analyze data accuracy and models’ performance.
Demonstrate software to customers and perform value proving benchmarks. Calibrate software for customer needs and train customer for using and maintaining software.
Resolve customer complaints with software and respond to suggestions for improvements and enhancements.
Required Qualifications
Advanced Degree in Statistics, Operations Research, Computer Science, Mathematics, or Machine Learning.
Proven ability to apply modeling and analytical skills to real-world problems.
Knowledge of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and statistical concepts (regression, properties of distributions, statistical tests, etc.).
Solid programming skills 2-3 languages out of R, SQL, Python, TensorFlow, PySpark, Java, JavaScript or C++.
Absolutely must have: graduate school level knowledge of Revenue Management models and algorithms.
Experience (minimum 4 out of 7) with deployment of machine learning and statistical models on a cloud:
- Mlops within the enterprise CI/CD process for ML models – 2 years
- Experience deploying ML APIs in production environments in GCP using GKE – 2 years
- Experience in using GCP Vertex AI for ML and Big Query – 1 year
- Knowledge in Terraform and Containers technologies – 2 years
- Experience writing data processing jobs using GCP Dataflow and DATAPROC – 2 years
- Experience setting up ML model monitoring and autoscaling for ML prediction jobs – 1 year
- Understanding of machine learning concepts to scale ML across different services by leveraging Feature Store, Artifacts Registry and Analytics Hub – 1 year Desirable Qualifications
Familiarity with airline, hospitality or retailing industries and decision support systems employed there.
Experience developing customer choice models, price elasticity estimation and market potential estimation.
Understanding of airline distribution, pricing, revenue management, NDC and Offer/Order Management concepts.
Carrier Ladder
Job Type: Contract
Pay: $75.00 - $80.00 per hour
Expected hours: 40 per week
Schedule:
8 hour shift
Experience:
Data Scientist: 9 years (Required)
Airline Revenue Management: 3 years (Required)
Google Cloud (GCP): 6 years (Required)
Python: 7 years (Required)
C++: 4 years (Required)
PySpark: 6 years (Required)
Rally: 5 years (Required)
JIRA: 8 years (Required)
Work Location: Remote
