Trainee Data Scientist

Summary

Join Rackspace Technology as a Data Scientist and contribute to the development of analytical models that drive impactful business decisions. You will experiment with and implement machine learning techniques on diverse projects, while staying current with the latest data science advancements. Collaboration and independent work are key aspects of this role, requiring you to contribute to team discussions and deliver results on schedule. This position demands proficiency in machine learning, statistics, programming languages (Python/R/SAS), SQL, data visualization tools, and cloud computing platforms. Rackspace offers a supportive and inclusive work environment, recognized as a best place to work by various publications.

Requirements

• Possess a Degree in Management Information Systems (MIS), Data Science/Analytics, Computer Science, Statistics and/or equivalent formal training
• Be proficient with machine learning and statistics
• Have knowledge in classification (random forest, logistic regression), regression (linear, XGBoost) and clustering (k-means)
• Possess software development experience
• Be proficient in Python/R/SAS, SQL, Data Visualization (e.g. Tableau or Power BI), deep learning frameworks, Spark
• Have excellent communication skills
• Be proficient with cloud computing in environments such are AWS, Google Cloud, Microsoft Azure

Responsibilities

• Develop analytical models for insight generation that improves business decision making
• Experiment with and implement machine learning techniques on internal/external customer projects
• Learn new data science techniques/programming languages and explore their viability on current projects
• Contribute to data science team discussions, providing insight on current approaches and methods
• Follow established MLOps practices in software development
• Perform data science model selection and implementation
• Work independently while collaborating well within the team
• Work autonomously and deliver results on schedule

Preferred Qualifications

• Have participated in numerous data science projects
• Have utilized several data science methodologies
• Possess attention to detail
• Be able to multi-task
• Possess strong analytical skills