Role Overview
- Utilizes basic knowledge to apply analytics and modeling techniques to improve business results.
- Performs routine assignments and leverages customer information and behavioral data to influence strategic business decisions.
- Uses analytics, multi-variate models, machine learning and data mining technologies.
- Actively learns about business operations and best practices in data science with guidance from more senior roles.
Requirements
- Utilizes conceptual knowledge of consumer analytics including retention models, agency economics, and lead optimization in their daily work.
- Utilizes basic knowledge of programing, ETL and modeling methods to execute projects and assists the team through examples of good technical skills.
- Executes on low-complexity business challenges involving data science.
- Succeeds in projects by utilizing a data science vision for project success, and accomplishes successfully within prescribed timelines.
- Executes on routine projects with a sense of urgency.
- Contributes to development of presentations.
- Occasionally communicates complex technical material understandable to non-technical associates.
- Executes basic to intermediate model deployments via established MLOps techniques.
- Works with analytics and IT teams to deploy models/rules.
Technical & Business Skills
- 1+ years of experience working in a Data environment
- Basic knowledge of data analysis, manipulation tools such as Python.
- Understanding on statistics in modeling side.
- Strong verbal communication and listening skills.
- Demonstrated written communication skills.
- Demonstrated time management and priority setting skills. with some guidance.
- Developing ability to consult on data extraction, data manipulation and data design for statistical, modeling and monitoring needs with guidance.
- Able to adapt quickly to new technologies.
Nice to have
- Proficiency working on large-scale structured and unstructured multidimensional data using conceptual knowledge of open-source cloud-enabled analytical programming languages.
- Basic proficiency in predictive and prescriptive modeling using advanced machine learning and deep learning techniques.
- Conceptual knowledge of ML/AI model deployment best practices.
- Conceptual knowledge of coding standards and version control (Git).
Tech Stack
Benefits
- A competitive salary and performance-based bonuses.
- Comprehensive benefits package.
- Flexible work arrangements (remote and/or office-based).
- A dynamic and inclusive work culture within a globally renowned group.
- Private Health Insurance.
- Paid Time Off.
- Training & Development opportunities in partnership with renowned companies.