Full Stack Data Scientist- The Next Big Thing

Full Stack Data Scientist- The Next Big Thing

1-Who is a full stack data scientist?

A full-stack data scientist is a unicorn who is capable of fulfilling the role of a software engineer, data engineer, business analyst, machine learning engineer, and data scientist, all wrapped up in one package. These individuals have diverse skill sets beyond even that of a regular data scientist and could be a company’s one-stop shop for managing the entire lifecycle of a data science project.

2- Skillset required to become a full stack data scientist:

• Maths/Statistics: They possess a strong foundation in mathematical and statistical concepts, using data science principles to derive valuable insights.
  Machine Learning: From constructing predictive models to fine-tuning deep learning architectures, they boast a broad repertoire of machine learning techniques.

• Deployment and MLOps: Going beyond model building, they possess the expertise to deploy models into production environments and integrate machine learning operations seamlessly.

• Data Engineering: These experts excel at data acquisition, storage, and processing. They are adept at gathering data through web scraping, utilizing data APIs, and leveraging databases for comprehensive analysis. They design and implement data pipelines to effectively handle complex data sources.

• Data Visualization: Full Stack Data Scientists possess the art of translating intricate insights into compelling visualizations, enabling stakeholders to make data-driven decisions.

• Business Action: Beyond technical prowess, their ability to effectively communicate complex findings and data stories to non-technical stakeholders empowers data-driven decision-making throughout organisations.

Do you think the transition from a data scientist to a full stack data scientist is easy and is it worth it?

Adapted from: Mahnoor Salman