Why Data Science Matters

There is a huge demand for data scientists to mine data for insights. It has led product teams to use data to focus on four specific outcomes. 

• Evaluating the health of a product or business by monitoring the metrics to ensure you are on the right track.
• Ensuring that the right products and features get built. Typically data scientists help design experiments and identify data-Informed hypotheses on phenomena.
• Forecast outcomes and Power production systems. Data scientists train machine learning models of a phenomenon to forecast future trends.
• Set roadmap and strategy for the product.

Data scientists have multiple roles that vary across companies and industries. Generally, there are two main types of data scientists.

• Product analysts focus on setting goals and informing product strategies. They help improve products by evaluating their health and providing product decisions.
• Algorithm developers. Their main task is to use the data to improve product performance. They mainly use machine learning and other algorithmic techniques to make predictions.

In summary, product analysts are data-informed, while algorithm developers are data-driven.