Key responsibilities
- Deliver quality analytics, from data preparation, data analysis, data exploration, data quality assessment, data manipulation, method selection, design & application, insights generation and visualisation
- Intensive learning and acquisition of key analytical, technical and commercial skills and business knowledge to become a proficient Analyst working under the supervision of the senior analysts/lead analysts.
- KPIs Timeliness, accuracy, manager and client feedback (Internal and external as required)
- Collaborate ,with internal stakeholders and demonstrate the ability transform client questions and problems into analytical solutions
- Active team member in providing the required support to help business understand and optimise use of analytical products and / or solutions
- Build industry knowledge on the advancements in the field of analytics
- Comply with the IM Cigna and CHSI Policies, procedures and processes, and continuously demonstrate Cigna Data and Analytics culture.
Key activities
- Working in a team to support end-to-end analytical projects
- Liaising with stakeholders to determine objectives / scope of upcoming projects
- Data exploration, cleansing and manipulation
- Determining appropriate type of analysis and undertaking analysis
- Extracting insights
- Clear presentation of insights via spreadsheets, PowerPoint presentations, self-service analytical visualisation tools
- Participate in client meetings
- Ongoing stakeholder interaction (internal and external as required) on project progress
- Contribute to the Feedback process (between stakeholders and the team) to ensure continuous improvement with team
- Participate and contribute in learning forums such as Analytics Community and sharing knowledge with wider team
Experience and education required
- 2-4+ years experience in a technical analytics environment, carrying out data analytics
- Tertiary qualifications in engineering, mathematics, actuarial studies, statistics, physics, or a related discipline
- Knowledge of technical analytics discipline, including data preparation and foundational analytics concepts
- Experience with successfully managing both internal and external stakeholders, delivering against projects, tasks and activities in a dynamic deadline driven environment
- Commercial acumen to understand business needs and be able to suggest the commercial impacts of different analytics solutions or approaches
- Coding and modelling experience in SQL / R / Python and / or Cloud data platforms e.g. AWS
- Experience in visualization and data management tools is an added advantage
- Experience in GenAI/ LLMs is an added advantage
- Experience working with complex datasets
- Attention to detail
- Drive for continuous improvement
- Participation in external data hackathons and competitions will be an added advantage
