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Data Science Career Ladders

Data science is generally a new department within companies, but some companies have begun to create leveling guides to help team members chart the skills needed to advance their career and grow across levels with objective guidance.
What You'll Learn

  • How to Think About Data Career Paths

    Data career paths are varied and complex, requiring a strategic approach to navigate. A clear understanding of the industry, skills, and personal goals is essential to succeed.

    • Metromile logo
      Everything You Need to Build Your Own Data Science Career Ladder

      George Bezerra, VP of Data Science, Metromile

      George provides details on individual contributor and management tracks for data scientists, along with descriptions of 49 skills within 12 skill categories. At the bottom of the article, George provides a link to a sample data science skill matrix.

    • Eventbrite logo
      The Analyst Career Path

      Casey Winters, CPO, Eventbrite

      The data analysis department is generally smaller than departments like engineering and product management, which leads to more questions about how to progress through a data analysis career. Casey provides 3 career pathway options based on his experience managing data analysts: • Option 1: Graduate into Data Science • Option 2: Become an Analytics Manager • Option 3: Graduate into Product Management

  • Data Skill Groups

    Data skill groups encompass a broad range of competencies, including technical, business, and soft skills. These groups are essential for developing a well-rounded data professional.

  • Data Analytics Career Ladders Examples

    Data analytics career ladders offer a clear path for professionals to progress from entry-level to senior positions. These ladders typically involve mastering specific skills and taking on increasing levels of responsibility.

  • Data Science Career Ladders Examples

    Data science career ladders are similar to analytics ladders but require a deeper understanding of statistics, programming, and machine learning. These ladders often involve transitioning from a more technical role to a leadership position.

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