Job summary

Location:
Cape Town, South Africa, Africa
Career Level:
Senior (5+ years of experience)
Education:
Bachelor's Degree
Job type:
Full time
Positions:
1
Salary:
Negotiable

Data Scientist - Intermediate AA/EE (Cape Town) (Ref 117)

About this job

Overview: As part of our client’s Analytics and Optimisation team you will use statistical analysis, predictive modelling and machine learning within analytical strategy design to solve real-world problems. You will be required to manipulate, clean, validate and analyse existing structured and unstructured datasets, (large and small and from a variety of sources), as well as create new data that will add value to the data mining function. By monitoring and evaluating implemented strategies and models you will then be able to communicate your findings and make recommendations to stakeholders across the client’s business.

In line with our client’s transformation plan, suitably qualified African Black (AB) candidates who meet the criteria for the role will be given preference.

Qualifications, Experience and Skills
Degree within a quantitative discipline (i.e. Statistics, mathematics, actuarial sciences)

4yrs Experience analysing and interpreting quantitative and qualitative data
4yrs Experience in building predictive models (classification and regression) essential, machine-learning approaches, clustering and classification techniques, and recommendation and optimization algorithms.
2yrs Experience in a similar environment within Financial Services environment 
4yrs Experience in a variety of predictive modelling scenarios advantageous (acquisition modelling, churn modelling, cross-sell and up-sell models, next best action systems, uplift modelling, segmentation etc.)
3yrs Experience in analytical software i.e. SAS, R, Python
2yrs Knowledge of SQL and relational databases advantageous.
Ability to work with unstructured data.
2yrs Data wrangling/data manipulation
Analytical strategy design advantageous. Deriving value from the models, making models actionable and investigating impact of moving from one model (or set of models) to another.
3yrs Experience in practical implementation of theoretical models.
2yrs Experience with big data platforms advantageous – Hadoop, Hive, Pig, Amazon S3

 

 



Duties

Job Function

Data Manipulation and Creation
Conceptualise, design/source (and where appropriate, evaluate) and implement relevant infrastructure to deliver strategic data intelligence for market research
 
Continuous performance monitoring and improvement of data infrastructure (including evolving data warehousing needs), systems and processes etc. in accordance with business
Preparation of data for modelling – transforming real-world data into formats usable in statistical software tools, through SQL or other data manipulation software

Build predictive models
Build data driven models to abstract customer behaviour using a variety of predictive modelling techniques.

Model implementation
Work with technical resources to support implementation of theoretical models into real-world business application
Manage output from predictive models

Analytical Strategy Design
Derive, abstract and quantify business constraints
Utilise predictive assets/models to facilitate optimal decisions on a customer and macro level across customers’ lifecycle

Model maintenance, reporting and analysis
Track performance of models and monitor for deterioration
Report back on model performance and recommend appropriate courses of action to counter deterioration
Conduct root-cause analysis where predictions diverge from actuals


 

Business Engagement 
Act as the business owner for outputs generated from predictive models
Build and maintain effective working relationships with internal (BI, Data, Marketing and Credit Risk) and external stakeholders to provide the business with relevant and useful analytics by providing expert knowledge and engaging around data intelligence.
 
Deliver value-adding, informed, strategic recommendations and insights through effective collaboration with stakeholders, applying best practice statistical and data intelligence techniques
 
Proactively investigate opportunities for business growth and improvement, based on informed data intelligence
 
Evaluate marketing strategies against data intelligence and defined business objectives
 
Influence stakeholders to obtain buy-in for concepts and ideas, and working with a group to brainstorm ways of improving a product or situation and to identify alternative solutions to a problem .

Ad hoc analysis
Work on ad hoc descriptive and predictive analytical projects


Job keywords/tags:  Statistics , mathematics , actuarial sciences ,
Developed by Figo Mago at www.tandolin.co.za
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