0-2 years of professional experiences in Data Science fields.
Mandatory: Experienced using programming languages (at least Python and SQL) to manipulate data and draw insights from large data sets.
Intermediate Mathematical, Statistical, and/or Machine Learning skills required, and their real-world advantages/drawbacks.
Knowledge and/or experience in working with structured and/or unstructured data sets.
Knowledge and/or experience in Data Architecture and Engineering is a plus, especially Google Cloud Platform.
Familiar with Data Visualization Tools, Google Data Studio is a plus.
Character
Problem-solving skills, structured thinking and scientific approach required.
Ability to work with minimal supervision and keep supervisors informed.
Ability to work well in a team environment.
Ability to communicate in clear and concise terms.
Willing to learn new skills and able to do so independently.
Ability to take initiative.
Assist in methodology research, data processing, and documentation to conduct independent self-guided exploration of research and frame open-ended industry questions, including, but not limited to:
Conducts statistical analyses to develop strategies,
Builds predictive models and machine-learning algorithms,
Identifies data patterns and trends,
Proposes solutions and strategies to business challenges,
Presents information using data visualization techniques, and
Documents all processes and research.
Discover new opportunities to optimize the business through machine learning and/or statistical modelling.
Assist the design and development of analytical projects designed to understand key business behaviors that drive customer acquisition, retention, and engagement through machine learning and/or statistical modelling.
Assist in implementation of client’s analytics solutions with internal Project Coordinator.
Develop and maintain client analytics reports.
Leadership Responsibilities:
Commits to personal learning and growth.
A drive to learn and master new technologies and techniques.