Specialist Business Intelligence Analyst - Corporate Investment Banking

SUMMARY:
Leverage deep data science expertise in advanced statistics, data wrangling, data mining, data analysis, feature engineering &predictive modeling

POSITION INFO:

INTRODUCTION:

Leverage deep data science expertise in advanced statistics, data wrangling, data mining, data analysis, feature engineering &predictive modeling, storytelling, distributed computing & data visualization, machine learning tools & data intuition to define, build, operationalize & continuously improve data solutions that deliver relevantly, quality-assured, accurate & commercially impactful data to the business. The role entails advanced Report development and data sourcing across the CIB Trade Finance space based on stakeholder requirements.

Critical Requirements:

• Qlikview Development
• MS SQL knowledge and writing scripts
• Ability to work independently
• Good communication skills

Optional Advantage:

• Hadoop, Scala, Python

Education and experience required:

• 3-5 years experience in Qlikview development
• Relevant B-Degree in Statistics, Mathematics, Computer Science OR; equivalent level of industry certification in Technical field
• 3-5 years experience manipulating data sets and building statistical models
• 3+ years experience working in a data environment – optimizing and building data sets with knowledge of & experience in one or more of the following areas relevant to the business being supported e.g. Qlikview
• 3+ years experience working in data environment – optimizing & transforming data by leveraging one or more of the following data science skills:
• Leveraging data pipelines and data sets
• Data Mining
• Data Optimisation
• Data Analysis & Interpretation
• Statistics
• Feature Engineering
• Predictive Modelling
• Distributed Computing
• Machine Learning
• Data Intuition
• Data Quality Assurance
• Excellent communication, analytical skills, and decision making ability in collaborative environments • Practical knowledge in mathematical & statistical software, databases and comfortable working with large data sets
• Experience and interest in relational database management systems / relational databases

Accountability:

• Participate in design thinking processes to determine & confirm hypotheses and priority questions/data challenges & related metrics to be solved for
• Translate business questions to be solved into data requirements & define data solutions to deliver against these requirements
• Proactively partner with the data engineering team to refine the data requirements deliver raw data to Data Science teams for interpretation & analysis
• A design fit for purpose data interpretation & analysis approaches & create customized data models, algorithms, machine learning tools, and recommendation engines to achieve the desired business outcomes
• Use advanced data science skills to mine & interpret data. These include but are not limited to: advanced statistics, data wrangling, data mining, data analysis, feature engineering & predictive modeling, distributed computing, machine learning tools & data intuition
• Analyze & interpret complex data sets
• Apply quality assurance frameworks to test model & analysis techniques (e.g. algorithms, models) & overall data quality
• Apply the testing frameworks to monitor and analyze model performance & data integrity on all data assignments
• Produce business insights and recommendations based on data analysis & modeling concluded & where relevant with knowledge and experience of e.g. Java, Scala, Python, Hadoop, Apache Spark & Kafka
• Use storytelling and data visualization techniques to maximize impact & deliver a user-friendly product to business
• Contribute to the consolidation of data solutions into viable end products (in the language of business) that can be leveraged on an ongoing basis e.g. dashboards, reports, etc.
• Present data analysis (trends, insights, forecasts) & findings to business & show tangible business impact to be derived from the data science process
• Facilitate peer reviews & feedback on data solutions
• Refine data analysis based on business & peer reviews
• Contribute to the assessments of the effectiveness and accuracy of new data sources & data gathering techniques
• Promote data literacy with your business stakeholders by sharing best practices and showing tangible business impact & recommendations as a direct result of the data solutions provided
• Stay ahead of the curve on data science trends & leading practice data science tools and techniques & transition the organization to advanced methods for the continuous optimization of data

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