|Job Title:||Data Scientist|
|Job Published:||April 25, 2017 10:43|
Job Title Data Scientist
Department Profit optimisation and Analytics
Type of employment Permanent
Part time / Full time Full time
Overview To use statistical analysis, predictive modelling and machine learning within analytical strategy design to solve real-world problems.
Manipulate, clean, validate and analyse existing structured and unstructured datasets, large and small, from a variety of sources, as well as creating new data that will add value to the data mining function. Monitor and evaluate implemented strategies and models. Communicate findings and make recommendations to stakeholders across the business
Requirements • Grade 12
• Degree within a quantitative discipline (i.e. Statistics, mathematics, actuarial sciences)
Experience • 3-5 years Experience analysing and interpreting quantitative and qualitative data
• 3-5 years Experience in building predictive models (classification and regression) essential, machine-learning approaches, clustering and classification techniques, and recommendation and optimization algorithms.
• 2-3 years Experience in a similar environment within Financial Services environment advantageous
• 3-5 years 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.)
• 3-5 years Experience in analytical software i.e. SAS,R, Python
• 3-5 years Knowledge of SQL and relational databases advantageous.
• 2-3 years Ability to work with unstructured data.
• 3-5 years Data wrangling/data manipulation
• 2-3 years 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.
• 2-3 years Experience in practical implementation of theoretical models.
• 2-3 years Experience with big data platforms advantageous – Hadoop, Hive, Pig, Amazon S3
Duties & Roles 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.
• 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
• 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
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