Data Analyst III/II/I

 1. Advanced knowledge of one or more differing statistical programming languages such as SAS, R or Stata.  

2. Ability to develop structure and/or program databases specifically within an MS SQL environment, skilled in the utilization of Structured Query Language (SQL) for interacting with data sets. Understanding of data structures and ability to become proficient in mining data structures and lineage in support of data foot printing and inventory techniques.  

3. Skilled in Robotic Process Automation tools such as UI Path and Artificial Intelligence tools like Data Robot  

4. Skilled in MS Office Suite including MS Access, Excel, PowerPoint, Word and MS SharePoint.  

5. Familiarity with the following disciplines

• Natural Language Processing: Interaction between computers and humans

• Machine Learning: using computers to improve as well as develop algorithms

• Conceptual modeling: to be able to share and articulate conceptual approaches to solving business questions/problems

• Statistical analysis and Predictive modeling

• Hypothesis testing: design hypothesis, document control and test with appropriate modeling and experimentation  

6. Ability to query databases and datasets and perform statistical analysis on enterprise-class database systems.  

7. Exceptional presentation skills.  

8. Being able to work in a fast-paced multidisciplinary environment as in a competitive landscape new data keeps flowing in rapidly and the world is constantly changing.  

9. Strong negotiation skills.  

10. Strong communication skills, including written, verbal and listening which can be deployed successfully when addressing entry level Colleagues to management to senior executives. This includes the ability to speak confidently in both business and technological surroundings and appropriately transliterate between the two.  

11. Exceptional analytical thinking and problem solving skills.  

12. Exceptional understanding of business and business strategy.  

13. Strong planning skills.  

14. Exceptional organizational skill and ability to work autonomously.  

15. Experience using data visualization tools such as QlikSense or Tableau  

16. Innovative curiosity  

17. Strong knowledge of Data Science 

18. Ability to deal with ambiguity  

Education Requirements:

Data Analyst III: Actuarial Designations can substitute for PhD. AFA specific data experience will be considered in lieu of PhD on case by case basis

Data Analyst I/II: High school diploma or equivalent