Data Analyst (9 months) #SGUnitedTraineeships
Income is strengthening its online presence for Life & General Insurance business. To scale up online sales capabilities & target customers with preferred product at preferred time, it's important to have personalized campaign design & provide them cost effective products through data driven solutions. Currently Income is working on Customer Interaction data model in datalake which will cater as main source of data for data discovery.
Income's customer data is stored at multiple & diversified operational & transactional systems. It's very important to provide a single view of customer to various business units like marketing, sales, actuary, operations etc. so they can have holistic view of customers, grow effectively by upsell/cross opportunities & at the same time provide better & timely service to customers.
To achieve this, Income embarked on data lake design & implementation of customer interaction data model. The objective of this project will be divided into three phases : a) Consolidation of various data sources & data model design into data lake (30% )
b) Solution for identified business problem through advanced analytics (50%)
- Data available & acquired for analysis like customer profile, transactional Info etc
- Data available but not yet acquired for analysis like financial portfolio, call logs, survey results, new online & offline interaction touch-points data etc
- Design scalable data model within datalake & expose data as a service
c) Timeliness of data availability to end users (20%)
- Analytics information like customer propensity score for micro-segments, Online & offline interaction analysis
- Recommendations like what product to buy, through which channel etc
- Design Lambda Architecture to process Batch & Real time for specific scenario
- Work on latest big data technology like Kafka Streaming, Storm etc & cloud providers like AWS, Google cloud
To scope the project, the initial analysis will be for Life or General Insurance products. Apply big data discovery & advanced analytics
techniques to know the customers better & act upon the new actionable insights to derive business value. It requires both business & technology acumen. Technical Skills and Competencies Trainee will learn during SGUnited Traineeship Programme:
- Trainee will work with the project manager to understand the business requirement, Ideate prototype & innovate solution design
- Trainee will learn CRISP-DM methodology. They will learn business domain & apply the knowledge in real world use cases
- Understand the insurance specific analytics design & framework
- Implement ETL workflow to ingest source systems data
- Learn advanced analytics techniques like feature engineering, pattern analysis, clustering, classification models etc.
- Implement spark jobs, apply best practises & learn debugging techniques etc.
- Deploying suitable & sustainable analytics model
- Trainee will mostly work on available open source software. Software may consist of MS SQL, NoSQL db, R, Python, Spark, Tableau and Hadoop Technologies.
- They will conduct design of experiment with available data & learn empirical model design. Trainee will demonstrate business value from data science project experiment.
- Highest Qualification: Degree in IT related field
- Eligibility Criteria for SGUnited Traineeships:
- Singapore Citizen or Permanent Resident; and
a. Graduated or graduating in calendar year 2019 or 2020 from Universities
b. Graduated earlier from above institutions and completed National Service in 2019 or 2020