Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.
Seeking a skilled and detail-oriented Data Analyst to support the audit and analysis of data within our Identity Platform. The ideal candidate will be responsible for gathering, processing, and interpreting audit data to ensure the platform's compliance, security, and operational efficiency. This role demands strong analytical skills, a thorough understanding of data governance, and the ability to communicate insights clearly to both technical and non-technical stakeholders.
Primary Responsibilities:
- Data Collection and Cleaning: Data Analysts are responsible for gathering data from multiple sources, ensuring its accuracy and completeness. This involves cleaning and preprocessing data to remove inaccuracies, duplicates, and irrelevant information. Proficiency in data manipulation tools such as SQL, Excel, and Python is essential for efficiently handling large data sets
- Analysis and Interpretation: One of the primary tasks of a Data Analyst is to analyse data to uncover trends, patterns, and correlations. They use statistical techniques and software such as R, SAS, and Tableau to conduct detailed analyses. The ability to interpret results and communicate findings clearly is crucial for guiding business decisions
- Reporting and Visualization: Data Analysts create comprehensive reports and visualizations to present data insights to stakeholders. These visualizations, often created using tools like Power BI and Tableau, make complex data more understandable and actionable. Analysts must be skilled in designing charts, graphs, and dashboards that effectively convey key information
- Collaboration and Communication: Effective collaboration with other departments, such as marketing, finance, and IT, is vital for understanding data needs and ensuring that analysis aligns with organizational goals. Data Analysts must communicate their findings clearly and concisely, often translating technical data into understandable insights for non-technical stakeholders
- Predictive Modelling and Forecasting: Advanced Data Analysts also engage in predictive modelling and forecasting, using machine learning algorithms and statistical methods to predict future trends and outcomes. This requires a solid understanding of data science principles and familiarity with tools like TensorFlow and Scikit-learn
- Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so
Required Qualifications:
- B.Tech or Master's degree or equivalent degree
- 10+ years of experience in Data Analyst role in Data Warehouse
- 6+ years of experience with a focus on building models for analytics and insights in AWS environments
- Experience with Data Visualization: Ability to create effective visualizations using tools like Tableau, Power BI, AWS Quick Sight and other visualization software
- Knowledge of Database Management: Understanding of database structures, schemas, and data management practices
- Programming Skills: Familiarity with programming languages such as Python and R for data analysis and modelling
- Proficiency in Analytical Tools: Solid knowledge of SQL, Excel, Python, R, and other data manipulation and statistical analysis tools
- Statistical Analysis: Proven solid grasp of statistical methods, hypothesis testing, and experimental design
Preferred Qualifications:
- Certification in data analytics, audit, or cybersecurity (e.g., CISA, CISSP, DA-100)
- Experience working in large-scale, cloud-based identity platforms
- Experience of Terraform to define and manage Infrastructure as Code(IaC)
- Proven ability to work independently and as part of a cross-functional team
- Demonstrated commitment to continuous learning and process improvement
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