Using data science to deliver value to our clients and business. This includes providing statistical analysis, forecasting, predictive modelling, simulation, machine learning and optimisation to discover trends, opportunities and threats.
Findings should be shared regularly with business users in a collaborative fashion.
Remain current with developments in data science technology and methodologies.
Must be proficient in ML language e.g. R, Python or Julia.
Must be proficient in SQL.
Develop models and work generally without supervision.
Establish effective and collaborative partnerships with other IT teams and provide technical and functional support.
Technical expert in ML languages (R, Python) and packages/techniques.
- Use statistical and other analysis methods to build and evaluate scorecards through standard methodology, data manipulation, checking results and presenting outcomes to both technical and non-technical audiences.
- Particular emphasis is on performing analytical work using CSH’s software (Modeller) and SAS/SQL.
- Ability to program efficiently and use appropriate naming conventions for all programs and files. Good programming practices should be adhered to, for example, using test data sets to test all programs before running on complete data sets and use of ongoing program flow diagrams. Completed projects are to be archived once a project has been signed off by a client to prevent network congestion, with a project summary sheet kept on the network for future reference.
- Responsible for ensuring scoring / analysis / statistical work is of high quality and professionally presented. Review of project at regular intervals and checking of all key correspondence and documentation.
- Write specifications giving clear and concise instructions. This includes project scope and data preparation specifications for application and behaviour scorecard developments.
- To converse in a professional manner with the client, whether face-to-face, over the telephone or in written communication e.g. e-mail at regular intervals.
- To prepare and present scoring demonstrations and presentations as required.
- Document analytic results, summarize findings and prepare client delivery materials and final documentation.
Product Demonstration and Training
- Develop a thorough knowledge of Modeller and the technical aspects of Scoring in addition to the skills required to demonstrate and present each of these products/services.
- BSc in a quantitative discipline such as Statistics, Econometrics, Operations Research or Mathematics (a graduate degree in similar fields is strongly preferred)
- Experience in manipulating large datasets. Working with large and diverse data files & Complex Data Analysis.
- Solid coding skills and knowledge of statistical software such as SAS, SQL etc.
- Demonstrate the ability of writing and presenting in English
- Strong attention to detail is a must.
- Good report writing skills.
- MS Office Suite to finalize specifications and project schedules.
- Presentation skills - Communicating information of technical nature to non-technical clients.
- Ability to elicit accurate information via a correct line of questioning.
- Ability to identify opportunities for process improvement and to enforce best practice.
- Listening skills.
- Ability to work effectively, independently and in a team environment.
- Ability to give constructive feedback.
- Solid foundation of analytics and modelling knowledge.
- Ability to interpret questionnaire responses and prepare proposals that are pertinent to the needs of the client.
- Knowledge of products and the relationship between products.
- Experience in a customer facing role.
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