DescriptionThe Data Visualization Engineer 2 builds user interfaces, visualizations, and data algorithms. Takes complex data and making it more accessible, understandable and usable for leaders to derive insights and ultimately enable them to make the better business decisions. The Data Visualization Engineer 2 work assignments are varied and frequently require interpretation and independent determination of the appropriate courses of action.
The Data Visualization Engineer 2 may work with stakeholders to perform data analytics and write software. Assists in the development of our cloud based analytics platform. Builds interactive visualizations and front end software applications for stakeholder engagement. Can perform analytics based on stakeholder needs. Understands department, segment, and organizational strategy and operating objectives, including their linkages to related areas. Makes decisions regarding own work methods, occasionally in ambiguous situations, and requires minimal direction and receives guidance where needed. Follows established guidelines/procedures.
Specific Job Responsibilities:
Develop expertise in DAI tools, including CoreMetrics, Hadoop for data query and exploration, Tableau for data visualization, R, Python, text analytics for reporting and visualization purposes.
Identify user friction points in their Humana digital experience (via data analysis) and communicate clearly these problems and next steps in recommended analysis.
Design, implement and maintain recurring reports, relying on multiple data sources to report on digital activity for individual business lines, customer experiences, visitor segments, and digital campaigns.
Collaborate across various Humana teams to provide actionable insights that enable Humana’s businesses to make data driven decisions to drive desired online consumer behaviors, improve the online digital experience, and optimize digital spend.
Build and document reporting requirements for digital programs based on business needs/objectives and identified data priorities
Develop and nurture collaborative partnerships with key stakeholders to identify questions that require data insights to answer, to enhance existing reports and to create new reporting.
Provide web analytics strategy and best practice guidance for Humana’s Digital COE and across the Enterprise.
Support data governance and best practice efforts across the organization.
Identify data gaps, find data sources to fill these gaps, make recommendations for additions to our DAI data environment.
Report on data inaccuracies and failures and participate in their resolution within DAI data environment.
Contribute to DAI Task Forces, short-term small teams that identify a competency gap/maturity need, and plan and execute solutions, then share out to entire DAI team.
Serve as Requirements Analyst and UAT tester for the build of new data sets into DAI data environment.
Develop and utilize best-in-class analytics and measurement methodologies in an environment that supports innovation; lead the analytics and insights capabilities for the department, including advanced visualization, streaming analytics and text mining
Apply innovative and scientific/quantitative analytical approaches to draw conclusions and make 'insight to action' recommendations to answer the business objective and drive the appropriate change. Translate recommendations into communication materials to effectively present to senior leaders. Incorporate visualization techniques to support the relevant points of the analysis and ease the understanding for less technical audiences.
Work to integrate (via enterprise data warehouse or other means) multiple and disparate data sources from a variety of systems, including, but not limited to web analytics, digital marketing, customer experience management, sales, social media listening, voice of the customer, and surveys with a goal to discover meaningful implications for businesses to make concrete business decisions
Influence the development, selection process, and ongoing support of system-wide analytic environments and tools
Determine and conduct appropriate exploratory data analysis (EDA) techniques on candidate data sets. Use appropriate sampling techniques to select data subset for EDA.
Build a robust capability in advanced analytics including regression analysis, conversion analysis, decision trees, attribution, and segmentation techniques.
Influence the strategy for testing, data analysis, measurement, and forecasting.
Create leading-edge analyses that uncover opportunities for website improvements, customer self-service, and sales.
Package and present analytical findings and communicate (both written and verbal) complex concepts to leadership at all levels. Succinctly deliver complex analysis/findings in a manner that conveys understanding, influences senior executives, garners support for recommendations, drives business decisions, and influences business strategy. Recommendations typically have a major impact on business results. Provide subject matter expertise in operationalizing recommendations.
Collaborate with stakeholders to gather, consolidate and validate business assumptions relevant to the solution strategy, prior to initiating and throughout the analytical process.
Identify analytic toolsets and manage vendor relationships
Identify and gather the relevant and quality data sources required to fully answer and address the problem for the recommended strategy. Integrate/transform disparate data sources and determine the appropriate data hygiene techniques to apply.
Document assumptions, methodology, validation and testing to facilitate peer reviews.
- Bachelor's Degree in Statistics, Mathematics, Computer Science, Engineering and/or related field
- 2-5 years of professional experience performing data analytics and building user interfaces, visualizations, and data algorithms
- Experience taking complex data and making it more accessible, understandable and usable for leaders to derive insights
- Clear oral and written communication skills
- Flexible, dynamic personality who works well in a team environment
- Individual contributor that can work independently
- Master's degree in Statistics, Mathematics, Computer Science, Engineering and/or related field
- Healthcare or managed care experience
- Experience with data extraction and analysis technologies such as SAS, SPSS, QlikView, Hadoop, SQL or similar tools
- Experience with reporting and creating metrics for management
- Experience with data mining, predictive modeling techniques and using data to drive business outcomes and decisions
Scheduled Weekly Hours40