Data Analytics Career Path

Being a “Data” Analyst is a well-paying and important job in the current data age.  A data analyst will retrieve and gather data, organize it and use it to reach meaningful conclusions.  It is believed that individuals with a math degree are needed the most for careers in data analytics. This includes but not limited to a long list of related job titles as follows.

Accounting Analyst
Budget Analyst
Business Analyst
Credit Analyst
Cost Analyst
Financial Analyst
Forensic Analyst
Inventory Analyst
Market Research Analyst
Operations Research Analyst
Rate Analyst
Project Analyst
Program Analyst
Quality Assurance Analyst
Risk Management Analyst
Securities Analyst

Requirements to Become a Data Analyst

A bachelor’s degree in mathematics or related fields is needed for most entry-level jobs, and a master’s degree in statistics or related fields will be needed for many upper-level jobs. At UMKC Math and Stat Department we have created a career path for those who are interested to become a data analyst. Below is a list of  recommended courses that provide the necessary  skills for careers in Data Analytics.

  1. STAT 235 Elementary Statistics (3 credit hours)
  2. STAT 240 Introduction to Data Visualization (NEW COURSE, 1 credit hour)
  3. STAT 245 Introduction to Diagnostic Analytics (NEW COURSE, 1 credit hour)
  4. STAT 260 Introduction to Predictive Analytics (NEW COURSE, 1 credit hour)
  5. COMP-SCI 101 Problem Solving and Programming I (3 credit hours)
  6. COMP-SCI 101L Problem Solving & Programming I Lab (1 credit hour)
  7. COMP-SCI 191 Discrete Structures I (3 credit hours)
  8. Math 314 Graph Theory with Applications (NEW COURSE, 3 credit hours)
  9. GEOG 444 Spatial Data Analysis (3 credit hours)
  10. DSOM 311 Business Analytics II (3 credit hours)

Additional courses to consider:

  1. MKT 390 Customer Data Analytics (3 credit hours)
  2. ECON 425 Intermediate Economic Statistics (3 credit hours)
  3. STAT 496 Internship/Practical Training in Mathematics or Statistics (1-3 credit hours)
  4. STAT 436 Introduction to Mathematical Statistics I (3 credit hours)
  5. STAT 441 Introduction to Mathematical Statistics II (3 credit hours)
  6. COMP-SCI 394R Applied Probability (3 credit hours)

For more information please contact Dr. Bani-Yaghoub (