Salary
💰 $93,500 - $124,200 per year
Job Level
Mid-LevelSenior
Tech Stack
CloudPythonSQL
About the role
- Analyze and model airline operations and/or customer data and implement algorithms to support analysis using advanced statistical, engineering, and mathematical methods.
- Interpret business opportunities into Data Science projects and deliverables and quantify ROI/Business impact.
- Translate advanced analytics problems into technical approaches yielding actionable recommendations across predictive maintenance, delay predictions/recovery, and product upselling/cross-selling.
- Communicate results and educate stakeholders through visualizations, reports and presentations.
- Facilitate team collaboration to remove impediments and empower self-organization and productivity improvements.
- Retrieve, prepare, and process a rich variety of data sources from structured/unstructured cloud and non-cloud sources.
- Perform exploratory data analysis, generate and test hypotheses, and uncover trends and relationships.
- Act as an analytical mentor and help establish and sustain Data Science culture.
- Document approaches and model metrics and provide cohesive end-to-end solutions across technology, engineering, and commercial verticals.
- Other duties as assigned.
Requirements
- Combination of Education and Experience will be considered.
- Must be authorized to work in the US as defined by the Immigration Act of 1986.
- Must pass a Criminal Background Check.
- Bachelor’s Degree from an accredited college/university in Computer Science, Statistics, Mathematics, Engineering, Bioinformatics, Econometrics, Physics, Operations Research or related field.
- Minimum of three (3) years of experience in a technical environment.
- Understanding of applied Statistics, algorithms, modeling techniques as they relate to Data Science as a practice.
- Technical experience working with data to include sourcing, extracting, validating, exploring, and transforming data with tools like SQL and Python.
- Expert knowledge of the Data Science process.
- Initiative, curiosity, and problem-solving skills through personal development projects and ongoing education.
- Command of Python and/or R with the ability to mentor and train others.
- Command of SQL with the ability to mentor and train others.
- Ability to lead, manage and deliver complex Data Science projects with minimal oversight.
- Command of applied statistics for Data Science.
- Master's Degree or PhD (listed as preferred and also mentioned).