Data Scientist II

Summary

The Data Scientist turns data into high value assets in the form of insights and predictive models that contribute to measurable improvements in business process and performance. The Data Scientist II is expected to work independently with minimal oversight as well as lead project initiatives, mentor and assign work to others as needed. This role requires strong understanding and experience in Applied Statistics for Data Science as well as expertise in data wrangling, building, deploying and maintaining predictive models.

You will be responsible to ensure the rest of the team and stakeholders engage in best practices to ensure statistically sound deliverables. You will document best practices as well as lead peer reviews of Data Science work. You will deliver improvements to existing models as well as lead ongoing complex initiatives for revenue optimization, customer segmentation, media‑mix optimization, and churn analysis.

Visa Sponsorship Available:
No

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.

• Education:
  
  Bachelor’s Degree from an accredited college/university in one or more of the following:
  Computer Science, Statistics, Mathematics, Engineering, Bioinformatics, Econometrics, Physics, Operations Research or related field.
• Minimum of three (3) years of experience in a technical environment.
• Other Requirements:
  • 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.

• Master's Degree or PhD.
• Strong knowledge in one or more of the following fields: statistics, data mining, machine learning, simulation, operations research, econometrics, and/or information retrieval.
• Strong knowledge of the data science process and practical experience using machine learning algorithms including regression, classification, simulation, scenario analysis, modeling, clustering, and decision trees.
• Knowledge in airline operations, customer interactions and/or inter‑departmental limitations across business units.
• Strong written and verbal communication skills, proven presentation skills to all levels of audience.
• Strong intellect and analytical aptitude, along with ability to be self‑driven.
• Demonstrated proficiency in Python, R, MATLAB, SQL or other programming languages or packages.
• Comfortable with a fast paced, dynamic work environment.
• Strong computer skills including but not limited to MS Office products.

• Analyze and model airline operations and/or customer data and implement algorithms to support analysis using advanced statistical, engineering, and mathematical methods from physics, machine learning, data mining, econometrics, and operations research.
• Interpret business opportunities into Data Science projects and deliverables. Deliver Data Science solutions and quantify ROI/Business impact.
• Translate advanced analytics problems into technical approaches that yield actionable recommendations, in diverse domains such as predictive maintenance, delay predictions/recovery and Allegiant products upselling/cross‑selling; communicate results and educate stakeholders through insightful visualizations, reports and presentations.
• Facilitate conversations for teams to collaborate in removing impediments, empowering teams to self‑organize and improve their productivity.
• Retrieve, prepare, and process a rich variety of data sources from structured/unstructured cloud and non‑cloud sources.
• Perform…