Specialist -“ Data Science
Abu Dhabi, UAE
منذ 16 يوم

Expiry Date : 2018 / 08 / 04

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Job Description

To identify business requirements, apply data science techniques / approaches (For example : pattern detection, graph and statistical analysis), set benchmarks and guiding principles and provide advice / guidance / decision logic to support the business to address business challenges and achieve desired outcomes

Data Science

Work with business stakeholders to identify business requirements and expected outcomes in order to model / frame meaningful business scenarios which impact critical business processes and / or decisions

Identify, acquire and prepare data including unstructured (e.g. pictures), semi structured (e.g. Tweets) and structured (e.

g. customer) using data wrangling methods in R, Python, SQL in infrastructure including SAS, Spark, Hadoop, NOSQL and relational database environments in order to provide decision logic

Recommend and explain to business users statistical and machine learning methods for problems (for example customers and market segmentation) in order to aid understanding and support achievement of business requirements / expected outcomes

Work with Data Architect to support data collection, integration and retention requirements based on input collected from the business and benchmark selected analytical models against best practices to ensure correct approach is being taken

Design experiments and test models in a real environment in order to measure business impact

Identify patterns and trends in data, analyse correlation and complex relationships in order to flag anomalies and outliers

Develop predictive forward looking models that pre-empt the likelihood of an outcome in order to support the business address business challenges in a proactive rather than reactive manner

Advice and Guidance

Liaise with external vendors to identify best practices for optimising data science infrastructure, reducing operational costs and improving system performance and provide advice / guidance to IT teams to ensure provision of data is optimised and delivers the best results

Derive ideas, insights, hypotheses and articulate to key stakeholders in non-technical / business terms how this can be used in order to address business challenges and achieve desired outcomes

Continuous Improvement

Suggest ongoing improvements to methods and algorithms that identify new information and findings in order to support the achievement of expected business outcomes

Liaise with external vendors, attend vendor presentations and conferences and conduct research in order to keep abreast of new and current machine learning and data wrangling techniques

Monitoring and Governance

Identify / evaluate the most effective way to derive value from available data, translate into guiding principles, set performance benchmarks / metrics and establish / implement a governance process to ensure maximum use / performance of available data

Policies, Processes, Systems and Procedures

Adhere to all relevant organisational and departmental policies, processes, standard operating procedures and instructions so that work is carried out to the required standard and in a consistent manner while delivering the required standard of service to customers and stakeholders


Manage self in line with the bank’s people management policies, procedures, processes and practices to ensure adherence and to maximise own contribution to business performance

Customer Service

Demonstrate Our Promise and apply the ADCB Service Standards to deliver the bank’s required levels of service in all internal and external customer interactions

Minimum Experience

At least 6 years of experience in data or statistical analysis, with mathematical and causal modeling skills

Minimum Qualifications

Bachelor’s Degree in Mathematics, Statistics, Computer Science, Physics, Economics or Operations Research

Professional Qualifications

TOGAF Certification or Equivalent

Knowledge and Skills

The ability to communicate with the business to understand requirements and present back findings and recommendations by demonstrating the potential value to the organization

The ability to identify solutions to loosely defined business problems by leveraging pattern detection over potentially large datasets

Programming skills, including Hadoop MapReduce or other big data frameworks, Java, statistical modelling (like SAS or R), SQL and depending on the scope of the project, text mining, machine learning or deep learning

Statistics skills such as distributions, statistical testing, regression

Storytelling with data

Data-modelling and information classification expertise at the enterprise level

Understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests

Ability to assess rapidly changing technologies and apply them to business needs

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