Associate Data Scientist
Job Description
The Data Scientist will take on a variety of tasks, including data analysis, modeling, machine learning, AI development, process automation, solving complex problems, and conceptualizing innovative solutions.
Skills:
- Strong mathematical & numeracy skills.
- Understanding of reporting & data visualization tools.
- Excellent analytical skills - the ability to identify trends, patterns, and insights from data.
- Experience building Machine Learning models using training data and test data.
- Quick learner – especially in the use of new applications/tools or analytical methods, can adapt quickly to different projects and situations, and can work on multiple projects concurrently.
- Excellent communication skills, both written and spoken in English.
Required Qualifications:
- Education Background: Bachelor’s degree in Information Technology, Computer Science / Engineering, Data Science, Mathematics, or Statistics
Experience:
- 2 years of experience required; If no work experience, internships or academic projects related to IT Service Management, Service Delivery, or IT Operations are beneficial.
- Exposure to ITIL or a project delivery framework is a plus.
- Core Technical Skills: Basic understanding of ITIL processes (particularly Service Transition and Change Management) and familiarity with Service Management tools such as Service Now, Jira, and Confluence.
Soft Skills:
- Strong communication, documentation, administrative, attention to detail, organizational, and problem-solving skills
Responsibilities Duties:
Responsibilities:
As an Associate Data Scientist, you will support the Data Scientist in the following tasks:
- Analyze huge amounts of data, both structured and unstructured
- Organizing data into usable formats
- Building predictive models
- Building machine learning algorithms
- Building AI-driven automations
- Analyzing data to generate insights for the internal service organization and customer reporting
- Setting up data infrastructure
- Assess the quality of data and remove or clean data.
- Generating information and insights from data sets and identifying trends and patterns
- Preparing automated reports for executive and project teams
- Create and automate visualizations of data.
- Present data using various data visualization techniques and tools.
- Investigate additional technologies and tools for developing innovative data strategies.