The Role

The Technology and Administration Solutions (TAS) team within WTW is looking for a passionate, creative, analytical data analyst who loves data, curious to explore and unveil insights to create a business story and reporting to influence key business decisions.

Key Responsibilities:

• Participate in team problem solving efforts and offer ideas to solve client issues

• Work with data engineers to ingest new data sources and operationalize dashboards

• Manipulate large data sets through statistical software or other methods

• Conduct relevant research, data analysis, and create reports

• Use visualization and machine learning techniques to produce business insights

• Produce actionable insights on how to improve our services and our clients’ customer experience

• Maintain responsibility for completion and accuracy of work products

• Communicate your findings in a clear, concise, and visual (when appropriate) manner to our key stakeholders

• Actively expand analytics and consulting skills through training courses, mentoring, and interaction with clients

• Bachelor’s Degree in Statistics, Business, or Data Science

• A strong background in applied statistics and/or machine learning – you should be self-directed when it comes to choosing an analysis approach given a research question and a dataset.

• Intermediate/Advanced working knowledge of large data manipulation and data mining techniques

• 1-3+ year(s) of experience with data quality analysis, statistical analysis and/or modeling.

• Experience mining and analyzing structured and unstructured data with competency in one or more of the following: R, Python, Tableau, PowerBI, or Alteryx

• Experience with SQL for querying relational databases

• Ideally Experience with dashboard design & development using Power BI or a similar tool such as Tableau

• Advanced Excel and PowerPoint skills

• Exceptional written and verbal communication and presentation skills

• Ability to work in a team environment that promotes collaboration

• Proven experience effectively prioritizing workload to meet deadlines and work objectives