1. 1 Seattle University Master’s of Science in Business Analytics Key skills, learning outcomes, and a sample of jobs to apply for, or aim to qualify for, a few years after graduation. (But last one may need a PhD.)

2. Quantitative Skills statistics data visualization data management data mining decision analysis risk analysis simulation programming optimization 2

3. Soft Skills data presentation communication business knowledge problem recognition, problem formulation metrics/KPI determination interpersonal persuasion 3

4. Learning Outcomes On successful conclusion of this program students will be able to: 1. Identify and describe complex business problems in terms of analytical models. 2.Apply appropriate analytical methods to find solutions to business problems that achieve stated objectives. 3.Translate results of business analytic projects into effective courses of action. 4.Demonstrate ethical decision-making in structured or unstructured and ambiguous situations. 5.Communicate technical information to both technical and non- technical audiences in speech, in writing, and graphically. 6.Exhibit effective collaboration and leadership skills. 4

5. Statistician/Analyst K.C. Royals Advanced degree in math, stats, or related. (published research a plus) Up to date knowledge of statistical analysis techniques Experience with experimental design. Experience manipulating and analyzing large data sets. Knowledge of baseball and baseball data (Pitch f/x, Hit f/x, Field f/x). Excellent interpersonal and communications skills. Proficiency with the following tools and/or software: R, MATLAB, STATA, Minitab, or similar SQL or MySQL scripting Python, C++, or similar – preferred 5

6. Manager BAAmazon Master’s in Math, Finance, Statistics, Economics or related Relational database and SQL skills in Oracle, SQL Server, DB2. Experience developing complex statistical models. Working knowledge of machine learning and six-sigma. Skills presenting complex material to drive insight to leadership. Working knowledge of a statistical package such as R, Minitab, or SAS. 6

7. Sr. Data EngineerNetflix Ability to design and develop data structures needed to analyze large- scale complex business information. Strong SQL experience. Big data & production support ETL experience. Analytical tools for data analysis, reporting, visualization: Tableau, R, MicroStrategy. Pig and Hive / Python/Perl/Java/C++ Data modeling, SQL and data warehousing. Hadoop, MapReduce, Amazon EMR experience. You have taken classes or read books that give you an appreciation for basic stats and machine learning. You have dealt with TBs of data before. 7

8. Sr. Director Zillow Analytics Strong software engineering background with experience in analytic applications, machine learning and big data. Master’s or PhD in either computer science or heavily quantitative field. Experience building back-end services using Java, C++, C# or other OO languages. Java, Python, SQL, R. Hadoop, Spark, GraphLab, H2O. Machine learning. 8

9. Sr. Data Scientist Netflix Passion for translating unstructured problems into math framework. Ability to simplify mathematical models to make them practical. Knowledge of data structures and ability to write code. Ability to describe the logic and implications of a complex model. Predictive analytics/ statistical modeling/data mining. Multivariate Regression, Logistic Regression, Support Vector Machines, Bagging, Boosting, Decision Trees, Lifetime analysis, common clustering algorithms, Optimization, Stochastic Processes. Proficiency in statistical analysis tool such as R, SAS, and/or Weka. Above average capabilities with SQL. Distributed databases / query languages / general map reduce. 9