Job Purpose:
Reporting to Head Data Science, the Senior Data
Scientist will apply data mining techniques and conduct statistical analysis to
large, structured and unstructured data sets to understand and analyse
phenomena. Model complex business problems, discovering insights and
opportunities through statistical, algorithmic, machine learning and
visualisation techniques, working closely with clients, data and technology
teams to turn data into critical information used to make sound business
decisions. Execute intelligent automation and predictive modelling.
Responsibilities of the Senior Data Scientist:
Direct the gathering of data for use in Data Science
models, ensuring that chosen datasets best reflect the organisations goals.
Perform data pre-processing including data
manipulation, transformation, normalisation, standardisation, visualisation and
derivation of new variables/features.
Utilise advanced data analytics and mining techniques to analyse data, assessing data validity and usability; reviews data results to ensure accuracy; and communicates results and insights to stakeholders.
Designs various mathematical, statistical, and
simulation techniques to typically large and unstructured data sets in order to
answer critical business questions and create predictive solutions which drive
improvement in business outcomes. Drives analytics and insights across the
organisation by developing advanced statistical models and computational
algorithms based on business initiatives
Use data profiling and visualisation techniques using
tools to understand and explain data characteristics that will inform modelling
approaches. Communicate data information to business with various skill levels
and in various roles, presenting trends, correlations and patterns found in
complicated datasets in a manner that clearly and concisely conveys meaningful
insights and defend recommendations.
Create, maintain and optimise modelling solutions
that enable the forecast of quality data outcomes. Ensures that volumetric
predictions are modelled so that resource requirements are optimally
considered. Develops and maintains optimal evaluation techniques to ensure that
modelled outcomes are rigorous and creates model performance tracking. Drives
sustainable and effective modelling solutions.
Provide input into Data management and modelling
infrastructure requirements and adheres to the organisation’s infrastructure
development processes, including the management of User Acceptance Testing
(UAT). Conducts regression testing across all relevant systems as required.
Build machine learning models from and utilises
distributed data processing and analysis methodologies. Competent in Machine
Learning programming in R or Python, with supplementary still in Matlab, Java,
etc. Familiar with the Hadoop distributed computational platform, including
broader ecosystem of tools such as HDFS / Spark / Kafka
Act as a subject matter expert from a data science
perspective and provides input into all decisions relating to data science and
the use thereof. Educate the organisation on data science perspectives on new
approaches, such as testing hypotheses and statistical validation of results.
Ensure ongoing knowledge of industry standards as well as best practice and
identify gaps between these definitions/data elements and organisation data
elements/definitions
Qualifications and Experience:
Degree in Statistics, Machine Learning, Mathematics,
Computer Science, Economics, or any other related quantitative field.
5-7 years’ experience in working with unstructured
data (e.g. Streams, images) Understanding of data flows, data architecture, ETL
and processing of structured and unstructured data. Using data mining to
discover new patterns from large datasets. Implement standard and proprietary
algorithms for handling and processing data. Experience with common data
science toolkits, such as SAS, R, SPSS, etc. Experience with data visualisation
tools, such as Power BI, Tableau, etc.
Proficiency in application and web development.
Structured and Unstructured Query languages e.g. SQL, Power BI; QlikView;
Tableau; SSIS SSRS, R, Python, JSON , C#, Java, C++, HTML
Proven development experience in software and
software engineering. Understanding of financial services data processes,
systems, and products. Experience in technical business intelligence. Knowledge
of IT infrastructure and data principles.
Project management experience. Exposure to governance
and regulatory matters as it relates to data. Experience in building models
(credit scoring, propensity models, churn, etc.).
The candidate must also have a proven and successful
experience track record of leading high-performing data analyst teams leading
through the successful performance of advanced quantitative analyses and
statistical modelling that positively impact business performance.
A suitable candidate will also have had experience
working with and influencing and possess vast experience and expertise with
probability and statistics, inclusive of machine learning, experimental design,
and optimization. As a bonus he will also have had experience working with
Hadoop.
Communication Skills: Communication skills will also
be a necessity for the Senior Data Scientist. He must be able to convey
important messages and information down the line in order to ensure proper
exception of duties by junior data science personnel.
Ms Office/Software: Outstanding skills in the use of
Ms Word, Ms Excel, PowerPoint, and Outlook, which will all be necessary for the
creation of both visually and verbally engaging reports and presentations, for
senior data science management, executives, and stakeholders.
The candidate must also demonstrate exceptionally
good skills in SQL server reporting services, analysis services, Tableau,
integration services, Salesforce, or any other data visualization tools.
Technological Savvy/Analytical Skills:
Technologically adept and especially demonstrate an understanding of database
and computer software.
Interpersonal Skills: A suitable candidate for this
position will be a team-builder, be result-oriented, be proactive and
self-driven requiring minimal supervision, be open and welcoming to change, be
a creative and strategic thinker, have innovative problem-solving skills, be
highly organized, have an ability to handle multiple simultaneous tasks
prioritize and meet tight deadlines, and demonstrate calmness in times of
uncertainty and stress.
People Skills: A people person who is able to form
strong, lasting, and meaningful bonds with other people. This will make him/her
an approachable and trustworthy individual who junior personnel readily follow
and who Data and Analytics colleagues and stakeholders trust and who’s insights
they give credit to, making execution of his duties that much easier
How To Apply