1. Exploratory data analysis to understand customer struggles in the digital journey and create actionable insights through journey analytics

2. Deep-dive analysis using advanced statistical methods to understand the primary drivers behind customer struggles

3. Apply machine learning techniques to do customer segmentation, intelligent targeting and predictive servicing

4. Able to understand and solve the business problem by translating into a data model and building insights into an actionable outcome

5. Analyse experiment results and identify opportunities for improving experiment uplift; propose new experiment iterations based on the insights from the data

6. Support full lifecycle of experimentation (A/B testing) through journey analytics and machine learning driven insights

7. Collaborate with cross-functional business teams to deliver high-impact insights using analytics across a variety of customer servicing areas

8. Create visualization/dashboards for key metrics/insights

9. Verification/UAT of technology solution to ensure functional requirements are met

Requirements:

1. Curious and have a strong appetite for intellectual challenges. Able to pick up new methods and techniques quickly and apply towards solving a problem at hand

2. Attracted to a fast paced, hypothesis and test driven, collaborative and iterative environment

3. A good team player with excellent communication skills

4. A university degree or higher in Statistics/ Data Science/ Computing/Engineering, with a strong background in statistical concepts

5. Excellent hands-on experience in Python, Pyspark, Spark SQL/mysql

6. End to end data science workflow, starting from data extraction, wrangling, modelling and deployment in production environment

7. A good understanding of data analysis and machine learning, NLP concepts