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Data Science Career Roadmap: Jobs and Levels Guide
Explore the job-leveling matrix for Data Analysis careers. Understand the roles and skills needed to advance from beginner to leader.
May 17, 2024
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Data Scientist Resources
Explore our guides, templates, and tools for Data Scientists. Whether you’re an aspiring data scientist starting out or a senior data leader looking for a refresher, Coursera’s Data Scientist Resources will support you at every stage of your career.
Popular Data Science Courses
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Skills you'll gain: Dashboard, Data Visualization Software, Data Wrangling, Data Visualization, SQL, Statistical Methods, Plotly, Interactive Data Visualization, Jupyter, Exploratory Data Analysis, Data Mining, Data Cleansing, Matplotlib, Data Analysis, Generative AI, Pandas (Python Package), Data Manipulation, Regression Analysis, Seaborn, Professional Networking
Skills you'll gain: Jupyter, Automation, Web Scraping, Python Programming, Data Manipulation, Data Import/Export, Scripting, Data Structures, Data Processing, Data Collection, Application Programming Interface (API), Pandas (Python Package), Programming Principles, NumPy, Object Oriented Programming (OOP), Computer Programming
Multiple educators
Skills you'll gain: Data Engineering, Apache Airflow, Data Modeling, Data Pipelines, Data Storage, Data Architecture, Data Transformation, Requirements Analysis, Data Processing, Data Warehousing, Query Languages, Apache Hadoop, Extract, Transform, Load, Data Lakes, Amazon Web Services, File Systems, Database Systems, Data Integration, AWS Kinesis, Infrastructure as Code (IaC)
What are the top skills needed to be a data scientist?
Analytical skills: Analytics skills are crucial for data scientists as they enable them to transform raw data into actionable insights, driving informed decision-making to help solve complex business problems. Top skills include:
Programming Languages: Proficiency in languages like Python and R is vital because they provide the tools for data scientists to manipulate, analyze, and visualize large datasets efficiently. Top languages include:
Math & statistics: Mathematical and statistical knowledge is essential for designing experiments, assessing correlations, and optimizing algorithms to ensure precise and reliable outcomes in any data-driven project. Key skills to learn:
