Data Scientist with SAS Career Programme

The Pairview difference

Pairview is a specialist provider of career services and technical and management training. We concentrate on targeting the industry sectors where there are known skills-shortages, immediately putting you in demand. Our career path programmes produce highly talented individuals equipped to tackle the employment market.  We ensure that you get access to the very best career opportunities that your newly acquired and in-demand skills command.

Data Sciences with SAS – greatly rewarding career opportunities

56,000 Big Data jobs are expected in the UK by 2020, with demand for Data Scientists rising to 259%. However, employers are finding 75% of Data Scientist roles very hard-to-fill because of the shortage of people with the required skill-sets and experience. Data Scientists already command an average salary of £57,500 per annum and are able to boost their earning to £350 per day. (Source: Tech Partnership employers’ network, SAS, ITJobsWatch)

Pairview’s unique pathway to break into this great career

This programme is a senior level Data Scientist programme, specialising in the advanced uses of SAS such as statistical analysis, advanced multivariate regression modelling, cluster analysis and segmentation and other modelling and analytics methods. Most organisations rely on regression analysis in data mining to understand the interrelationships between dependant business variables and the impact it has on a specific business outcomes. As a statistical analyst able to utilise regression techniques to analyse multivariate data points, you will be in high demand in any industry and as a result most companies are prepared to pay the high premium salary for your services. Whilst this is not the full blown predictive modelling course, it is a step towards developing a career in predictive analytics. Here you will learn database management skills as well as advanced regression analysis. It is also an introductory to econometric modelling. After this programme you career might shape towards a role as a Statistical Data Analyst (£38,500 per annum), Lead Statistical Analyst (£45,000 per annum), or CRM Analyst (£50,000 per annum), and many more career paths using these skills, within the same range of salary. (Source: Indeed, ITJobsWatch)

On top of being equipped with the technical and knowledge-based skills in this programme, you will gain hands-on experience through our Work Experience Project, which will allow you to work on sample business scenarios and problems in sample businesses. You will receive the Work Experience Project at the end of the programme. The senior career programme’s Work Experience Project is longer than a typical project, lasting up to 3 months with 4 live sessions.

Your roadmap to career success in Data Sciences with SAS

1.       Microsoft Excel 2013 Core and Advanced Essentials | 3 days

You will learn how to:

• Create a basic worksheet by entering text, values, and formulas.
• Use the three-dimensional aspect of the Excel workbook environment
• Analyse data using a number of tools such as a subtotal report and a pivot table
• Confidently create an array of datasheets and worksheets to fit a range of purposes and outcomes

2.       Querying Microsoft SQL Server 2012 and T-SQL Programming | 3 days

You will learn how to:

• Describe the basic architecture and concepts of Microsoft SQL Server 2012.
• Understand the similarities and differences between Transact-SQL and other computer languages.
• Describe the use of data types in SQL Server
• Modify data using Transact-SQL

3.       Base SAS Introduction | 2 days

You will be able to:

• Understand file structure and write system commands to create and access files
• Understand programming logic concepts (IF/THEN logic)
• Understand the compilation and execution process of the DATA step
• Use different kinds of input to create SAS data sets from external files
• Use SAS software to access SAS data libraries
• Create and use SAS date values
• Read, concatenate, merge, match-merge and interleave SAS data sets
• Use the data set options DROP=, KEEP= and RENAME=
• Create multiple output data sets
• Use array processing and DO loops to process data iteratively
• Use SAS functions to perform data manipulation and transformations

4.       Statistical Analysis with SAS | 1 day

You will be able to:

• Use statistics to solve business problems
• Construct graphs to explore and report business information
• Assess the precision of your statistics
• Explore ways of testing business questions
• Explore relationships between variables
• Produce predictions of continuous target variables by fitting simple and multiple linear regression models
• Understand why categorised data are treated differently

1. 5.       Advanced Multivariate Regression Modelling with SAS | 1 day

• You will be able to:
• Support acquisition, retention and customer engagement programmes through propensity modelling and advanced analytics
• Offer insight into patterns, trends and relationships forming within organisational data-bases
• Provide customer insight profiling helping businesses get much closer to their customers and make relevant offers
• Build advanced statistical models to predict outcomes that drive strategic decisions
• Build customer value models that help determine customer contribution through various channels and product lines.

1. 6.       Customer Insight Analysis | 2 days

• You will be able to:
• Gain full understanding of what Customer Insight Analytics is all about and how this can be used to develop customer-focused strategy
• Evaluate and select appropriate research approach, whether internal data analysis or competitor intelligence is necessary to develop a solution for a given research contexts
• Support the development of marketing and consumer communication and research and insight process
• Develop market structure analysis to solve business problems where no pre-defined parameters exist. – Consultative business analytics
• Develop customer segmentation, including profiling and the development of strategic framework using segmentation approach
• Develop customer profile and interpret the meaning of such insight, i.e. create pen-portrait of customers.

7.       Hands-on Work Experience Project | 30 days

8.       CV Surgery | 1 day

9.       Project Support | 4 days

10.   Project Presentation | 1 day

11.   Interview Preparation | 3 sessions

You will need a graduate degree in one of the following majors: Mathematics, Physics, Engineering, Statistics, Computer Science, or from another similar technical/numeric discipline. A post-graduate degree in a technical discipline will be an advantage to help you drive a successful career in Big Data Analytics.

Basic working knowledge of Microsoft Office and Windows operating systems.

Data Scientist > Senior Data Scientist > Business Analytics Consultant