To provide data-driven insights that support the growth, optimization and performance of BluNest and other Digital Platforms through customer analytics, segmentation and product performance monitoring, while developing targeted, insight-led customer engagement communications and campaigns aimed at driving sales, revenue growth, customer acquisition, product adoption, engagement, retention and conversion. Monitor platform KPIs and growth metrics.Analyse investment product performance and adoption trends.Maintain dashboards tracking customer activity and conversion funnels.
Type of Qualification: First Degree
Field of Study: Statistics, Mathematics, Economics, Computer Science, Data Science, Engineering or related discipline.
- Experience with big data tools: Hadoop, Spark, Kafka, etc. Experience with relational SQL and NoSQL databases, including Postgres and Cassandra. Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc. Experience with AWS cloud services: EC2, EMR, RDS, Redshift. Experience with stream-processing systems: Storm, Spark-Streaming, etc. Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
- Strong analytic skills related to working with unstructured datasets. Build processes supporting data transformation, data structures, metadata, dependency and workload management. A successful history of manipulating, processing and extracting value from large disconnected datasets. Working knowledge of message queuing, stream processing, and highly scalable 'big data' data stores.
- Working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases. Experience building and optimizing 'big data' data pipelines, architectures and data sets. Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
Behavioural Competencies:
- Adopting Practical Approaches
- Articulating Information
- Challenging Ideas
- Checking Things
- Examining Information
- Exploring Possibilities
- Interpreting Data
- Meeting Timescales
- Producing Output
- Providing Insights
- Team Working
- Upholding Standards
Technical Competencies:
- Data Analysis
- Database Administration
- Data Integrity
- Information Technology Architecture
- IT Applications
- Knowledge Classification