Data Scientist-Dallas, TX

Data Scientist

Location: Dallas, TX - Hybrid Duration: 12 Months

We are looking for a Data Scientist to analyze large amounts of raw information to find patterns that will help improve Frontier. We will rely on you to build data products to extract valuable business insights. In this role, you should be highly analytical with a knack for analysis, math and statistics. Critical thinking and problem-solving skills are essential for interpreting data. We also want to see a passion for machine-learning and research. Your goal will be to help Frontier analyze trends to make better decisions.

Responsibilities:

• Provide analytical support and recommendations regarding optimization of operational processes, capital allocation, and pricing.
• Provide insights into future growth and profitability strategy through historical business analysis and forecasting of industry and major customer trends (e.g. what markets to prioritize, opportunities to pursue, how to win, impact of 5G, etc.)
• Work with and analyze complex data from various sources.
• Manipulate large data sets and navigate a variety of servers, data types, and data structures to complete statistical and other analyses
• Develop predictive and descriptive models using advanced procedures like statistical modeling, linear regression and Bayesian analyses.

Required Qualifications:

• Experience developing and implementing statistical models.
• Experience with a statistical analysis tool like Python.
• Experience performing data management, mining, and manipulation along with analytics.
• Experience using SQL in a RDBMS environment.
• Excellent communication skills, oral and written.
• Must have strong attention to detail and ability to work independently under general instructions and with a team.
• Some programming experience - This role will rely heavily on programming experience in Python, as well as SSMS.
• Degree (Graduate / Ph.D. preferred) in an analytical or technical field (e.g. applied mathematics, physics, computer science, operations research).