Data Scientist
Revenue Management Solutions
THE OPPORTUNITY
As a Data Scientist, you will have the opportunity to learn and apply RMS’ methodologies to solve analytical problems critical to driving high-end business value to our clients. This position requires an applied knowledge of Data Science and Deep Learning as well as demonstrating an ability to code in Python and SQL.
RIGHT TO WORK
Candidates must have the legal right to work in the country the position is based. The employer does not provide sponsorship for work authorization for this role.
WHO YOU’LL WORK WITH
You’ll work in our Tampa office as part of our Research & Development team, reporting to the Senior Director of AI and Machine Learning. You will work with the AI and Machine Learning team to develop machine learning or deep-learning models, perform exploratory data analysis, and apply data mining techniques. We take pride in encouraging each other’s career ambitions and you’ll find opportunities for personal development throughout our company. This is a hybrid position, working in the office 3 days a week.
WHAT YOU’LL DO
Implement scaled and systematic analytical solutions Build complex datasets and features stores from disparate sources
Create project plans, test various approaches, and evaluate results to answer key business questions
Creatively solve problems using quantitative and qualitative approaches to drive high-end business value
Develop documentation outlining methodology, feature engineering and model development
Engage and support internal teams to articulate processes and results
SKILLS AND QUALIFICATIONS
- Working Knowledge of statistics, machine learning/deep - learning, and data - mining algorithms
- Hands on experience coding in Python
- Experience working with large data sets
- Practical experience with Git and use of repositories for source control
- Strong interpersonal and communication skills, both verbal and written
- Ability to effectively manage simultaneous projects and deadlines
- Bachelor's degree in Economics, Mathematics, Engineering, Computer Science, or a field with a quantitative and technical emphasis required
PREFERRED
- Graduate degree, or supplementary courses in Statistics, Economics, Data Science or Data Engineering
Full Time
