Job Summary
To perform risk and securities administrative duties,
through the execution of predefined objectives as per agreed standard operating
procedures (SOPs).
Job Purpose
The role holder is responsible for applying data
mining techniques, doing statistical analysis, building high quality prediction
algorithms, developing analytical reports and devising analytical solutions to
use cases and data science problems. This will involve the ability to create
sophisticated, value-added analytic systems that support revenue generation,
risk management, operational efficiency, regulatory compliance, portfolio
management, and research.
Key Accountabilities
Perform statistical analysis, deploying models on
large data sets.
Conduct exploratory data analysis
Demonstrate strong understanding of agile delivery.
Develop code with Spark via PySpark or SparkR
Perform queries, aggregations, joins, and transformations using Spark, Hive, and Pig.
Develop new data sets using feature-engineering
techniques.
Deliver value by creating functions, classes, and
packages to automate processes and workflows for production deployment.
Evaluates user request for new/modified programs to
determine feasibility, cost and time required, compatibility with current
system, and computer capabilities.
Transform large, complex datasets into pragmatic,
actionable insights.
Leverage data to identify, quantify and influence
tangible business gain
Implement analytical model designs, perform any
restructuring required, and review dataset implementations performed by the
data engineer and BI developers.
Selecting features, building and optimizing
classifiers using machine learning techniques
Data mining using bank selected data mining tools
Enhance data collection procedures to include
information that is relevant for building analytic systems
Processing, cleansing, and verifying the integrity of
data used for advanced analysis
Doing ad-hoc analysis and presenting results in
reports, dashboards and charts
Creating automated anomaly detection systems and
constant tracking of its performance
Implement statistical data quality procedures or
test-driven approach for quality assurance
Challenge ideas and methods while working together
with talented, highly skilled team members.
Design, create, interpret and manage large datasets
to achieve business goals
Design, build, and maintain various parts of the data
warehousing with respect to requirements gathering, data modelling, metric
establishment, reporting production, and data visualization.
Gather and process raw, unstructured data at scale
into a form suitable for analysis then consolidate into the data warehouse in
order to perform Business Intelligence and advanced analytics.
Evaluate datasets for accuracy and quality using
statistical data quality procedures, software, or test-driven approaches that
ensure quality assurance and solve any issues, which may arise.
Improve data foundational procedures, guidelines and
standards and develop best practices for data management, maintenance,
reporting and security.
Conduct performance tuning to be able to optimize the
application of statistical models and scripts
Develop and maintain documentation/manuals on models
developed, reports generated and statistical solutions devised.
Carry out technical user training as required to
enable users interpret Data Science solutions
Ability to take personal responsibility and
accountability for timely response to client queries, requests or needs,
working to remove obstacles that may impede execution or overall success.
Assist in developing and implementing a program of
continuous improvement of Data processes through a cycle of analysis of
existing systems, processes, and tools, identifying areas for improvement, and
implementing high-impact changes, and getting feedback from stakeholders.
Understand Key Performance Measures and Indicators
that drive company performance measurement, reporting, and analytics across
functions and understand how these metrics and measures align and track against
overall business strategies, goals and objectives.
Work with Business Customers to understand business
requirements and implement solutions and with business owners to develop key
business questions and to build datasets that answer those questions.
Assist to analyze business/use case requirements from
BI analysts to determine operational problems, define data modeling
requirements, gather and validate information, apply judgment and statistical
tests and develop data structures to support the generation of business
insights and strategy;
Provide test interfaces for users to test the reports
and dashboards before being put on the production environment.
Preferred Qualification
B-degree in Mathematics/statistics, data sciences or
related quantitative fields is preferred (or equivalent on-the-job experience).
Preferred Experience
1-3 years Technical experience in data science.
Knowledge & Skills
Data-oriented personality
Knowledge of agile software development process and
performance metric tools
Experience extracting and cleaning text in different
formats e.g. HTML, pdf files
Proven ability to collaborate with other team members
across boundaries and contribute productively to the team’s work and output,
demonstrating respect for different points of view. Able to use strong
interpersonal and teamwork skills to cultivate effective, productive client
relationships and partnerships across organizational boundaries.
Knowledge on the Hadoop Data Platform and using Scala
for big data analysis
Proficient at queries, report writing and presenting
findings
Knowledge of ETL and data integration tools
Knowledge of merging technological trends in
programming languages and other programming tools
How To Apply