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Data Scientist

Revenue Management Solutions

Data ScientistAs 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.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.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 DoImplement scaled and systematic analytical solutions Build complex datasets and feature stores from disparate sourcesCreate project plans, test various approaches, and evaluate results to answer key business questionsCreatively solve problems using quantitative and qualitative approaches to drive high-end business valueDevelop documentation outlining methodology, feature engineering, and model developmentEngage and support internal teams to articulate processes and resultsSkills and QualificationsWorking knowledge of statistics, machine learning/deep-learning, and data-mining algorithmsHands on experience coding in PythonExperience working with large data setsPractical experience with Git and use of repositories for source controlStrong interpersonal and communication skills, both verbal and writtenAbility to effectively manage simultaneous projects and deadlinesBachelor's degree in Economics, Mathematics, Engineering, Computer Science, or a field with a quantitative and technical emphasis requiredPreferredGraduate degree, or supplementary courses in Statistics, Economics, Data Science or Data EngineeringBenefits100% employer paid HSA medical insurance, or 80% employer paid medical insurance for HMO and PPO plans for employees and qualifying dependentsDental and vision insurance (80% employer paid)Basic Life and AD&D insurance (100% employer paid)Telemedicine (100% employer paid)401k plan with company matching contribution of 4% of annual gross salary with immediate vestingTuition assistance is available to support continuous education efforts15 business days paid vacation for the first year based on your hire date (pro rata), 15 days thereafter; 20 days after two years, and 25 days after ten yearsEight paid holidays + 1 personal floating holidayPaid parking and health club membershipPaid parental leaveWho We AreNow more than ever, Revenue Management Solutions (RMS) is committed to supporting restaurants through these ever-changing times. Today, more than 50 major brands in over 40 countries trust RMS for data-driven analytics and tech-enabled solutions to optimize sales, menus, and a brand's financial health. Six of the top 10 US fast food brands and 16 of the top 30 global restaurant brands (equaling more than 100,000 restaurants) rely on RMS' software solutions and actionable insights to make informed business decisions that drive profitability and combat inflation and increasing wages. The company holds five US patents on menu pricing and customer segmentation and supports ongoing academic research efforts. For more information on how RMS helps its clients, visit revenuemanage.com.What We BelieveOur goal at RMS is to create a positive change in the communities we inhabit. With over 20 countries represented throughout our offices, we respect and embrace different cultures, interests, and actions. The acknowledgment of our unique identities is something that connects us across continents to uphold our values of diversity, respect, and responsibility.

Vacancy posted 1 day ago
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