Jobs for MSBA - Seattle University

download report

Transcript Jobs for MSBA - Seattle University

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.)
Quantitative Skills
data visualization
data management
data mining
decision analysis
risk analysis
Soft Skills
data presentation
business knowledge
problem recognition
problem formulation
metrics/KPI determination
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 nontechnical audiences in speech, in writing, and graphically.
6. Exhibit effective collaboration and leadership skills.
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
Manager BA
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.
Sr. Data Engineer
Ability to design and develop data structures needed to analyze largescale complex business information.
Strong SQL experience.
Big data & production support ETL experience.
Analytical tools for data analysis, reporting, visualization: Tableau, R,
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.
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
Experience building back-end services using Java, C++, C# or other OO
Java, Python, SQL, R.
Hadoop, Spark, GraphLab, H2O.
Machine learning.
Sr. Data Scientist
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.