As a self-starter, the person should be able to advanced statistical analysis to solve business problems. You should be able to discover patterns from vast amounts of data using data mining tools and weave these findings into actionable use cases / business insights.
- Be hands-on in developing descriptive / optimization models, such as: segmentation, customer networks, lifetime value, campaign optimization.
- Be adept with using advanced statistical analyses for problem solving.
- Be the go-to person for data cleaning, pre-processing, manipulation to convert data to usable forms.
- Be hands-on in developing predictive models, such as: Next Best action, churn predication, algorithmic pricing, market basket analysis.
- Be a self-learner: have a knack of learning new statistical concepts and technologies to come up with out-of-the-box solutions.
- Conceptualize business problems and use cases with the business team and come up with algorithmic solutions that are superior to rule-based ones.
Qualification & Experience:
- Bachelor’s degree in a quantitative field such as Management Sciences, Mathematics, Statistics, Economics, Engineering or Computer Science.
- 1+ years of experience, preferably in a data science / analytics role.