Career Advising Resources

Careers in Data Science

Career Paths in Data Science

Data Analyst

  • Curates insights from existing data 

  • Looking at the unknown from new perspectives

  • Programming languages like Python, R, SQL, HTML, JavaScript

  • Spreadsheet Tools (Excel) 

  • Data visualization like Tableau 

  • Identifying data quality issues and partialities in data acquisition 

  • Creating reports to help a business executive make better decisions 

  • Typical degree: Undergraduate B.S or B.A

Data Scientist

  • Can predict the future based on patterns, estimate the unknown 

  • Generates their own questions and then uses skillset to find answer

  • More advanced skillset of data visualization, advanced statistical techniques, and programming

  • Knows how to get the data that they need to perform the analysis they want 

  • Programming languages like Python, R, SAS, Matlab, SQL, Hive, Scala

  • Distributed computing frameworks like Hadoop

  • Big data packages like Spark, AWS

  • Machine learning skills 

  • Typical degree: Masters or PhD, sometimes Undergraduate degree depending on the company

Data Engineer

  • Builds scalable, high-performance data infrastructure for delivering clear business insights from raw data sources that the data scientists often interact with 

  • Tools: SQL, MySQL, NoSQL, Cassandra, and other data organization services

  • Advanced database and programming knowledge

  • Typical degree: Undergraduate or Masters with a degree in Computer science or engineering

Machine Learning Engineer

  • Develop algorithms that can receive input data and leverage statistical models to predict an output while updating outputs as new data becomes available 

  • Sits at the intersection of software engineering and data science 

  • Ensures that the raw data gathered from data pipelines are redefined as data science models that are ready to scale as needed

  • They feed data into models defined by data scientists

  • Can take theoretical data science models and scale them out to production level models that can handle terabytes of real time data

  • Skills: Python, Java, R, C++, C, JavaScript, Scala, Julia

  • General education requirements: Master’s or PhD in computer science, math, or statistics

  • Experience with vision processing, deep neural networks, Gaussian processes, and reinforcement learning 

  • Experience with distributed systems and messaging tools