Data Scientists are people who know how to extract meaning from and interpret data by using various tools and methods, like statistics and machine learning. They spend a lot of time in the process of collecting, cleaning, and munging data, because data is never clean. This process requires persistence, statistics, and software engineering skills—skills that are also necessary for understanding biases in the data, and for debugging logging output from code.
Whether you have no idea what you want to do, have a vague idea, or are ready to get started, we have the resources to help you get there.
Translate unstructured business problems into well-defined machine learning projects
Own all steps in ML/AI/Statistical model development cycle from ideation, hypothesis formulation, data collection, feature engineering, model development, and delivery
Develop advanced machine learning algorithms and translate complex analytics into actionable recommendations
Develop and prototype AI algorithms and software tools
Demonstrate thought leadership and expertise in ML/AI/Advanced Statistical methods to business partners (marketing, sales, and product)
Use data science to leverage data and create new products
Skills You'll Need
Experience working with scripting languages such as Python, R, and SQL
Fluent programming skills in Python and its many modules including Matplotlip, Numpy, along with the machine learning frameworks Tensorflow, Keras, and Sklearn
Expertise in machine learning algorithms with keen understanding of choosing suitable models, learning procedures, and working hyperparameters
Technical depth in the use of current state-of-the-art AI and ML technologies
Data Wrangling, Data Reporting, and Data Visualization
Industries You'll Work In
No items found.
The Network You'd Build
Here are a few real-word examples of jobs and people working in this industry right now.