Description:
Software Development house based in Johannesburg North has a vacancy available for a Data Analytics Specialist (predictive modeling, prescriptive analysis, machine learning, etc) with experience with data science model operationalization on-prem or in the cloud (GCP or Azure), to become part of their Insights and Analytics team.
This is a permanent in-house position with medical aid, a provident fund, group life, and a hybrid working model.
Reporting to: Insights and Analytics Manager.
Role Purpose:
To contribute excitedly and passionately to the Companies’ data-driven culture, helping the
business to generate meaningful value from data.
To partner with internal teams and external clients to deeply understand their needs, and
help to guide, design, and build robust, innovative, analytical solutions.
Central to the role is ensuring that all initiatives in the portfolio have measurable business
value and are prioritized accordingly.
Role Description:
● Engage with internal business clients with business questions, always probing for the
deeper questions and needs, to find the best possible solutions for the business.
● Play a key communication role between business and technical teams to ensure
business context is retained when building analytical and data-driven solutions.
● Build a deep contextual understanding of the business and the data to design and
propose new solutions that could add meaningful business value.
● Work closely with the data provisioning team to ensure they can provide the reliable,
consistent, and context-rich data assets that the team requires for data use cases.
● Create algorithms and build machine learning models to enhance product offerings
and solve business problems.
● Create monitoring and anomaly detection systems to track model performance.
● Presentation of data science opportunities and model outcomes to a variety of
stakeholders with a varied understanding of data principles.
● Management of client expectations through a high-level project plan, regular
interactions, and feedback.
Requirements:
Qualifications & Experience:
● Undergraduate degree/diploma in Mathematics, Statistics, Engineering, Physics,
Finance, or Economics (or similar).
● Knowledge and execution capabilities of common data structures, languages, and
tools (e.g. SQL (must), Python, or R (must).
● Experience or familiarity with data science model operationalization on-prem or in
the cloud (GCP or Azure preferred).
● Understanding and interpretation of statistics and data with a foundational
knowledge of regression analysis.
● An understanding (must) of Machine Learning techniques (supervised and
unsupervised learning). Practical experience preferred.
● Experience working in a high-paced environment, where prioritisation is essential.
● Experience working and interacting with a variety of stakeholders including
development technical, data engineers, sales, and customer experience teams.
● History of delivering small to large-scale analytics, data science, and business
intelligence projects that require extensive collaboration across multiple teams.
● A proven track record of data mining and data pre-processing to ensure quality work
delivery.
● Practical experience in BI reporting and data platforms including PowerBI (preferred),
Data Studio, and intermediate Microsoft Excel (must).
Knowledge and Skills:
● Strong data exploration, analytical, modeling, and reporting skills.
● Strong communication and people-engagement skills.
● Ability and desire to uncover the deep business questions and needs of clients.
● Keen attention to detail and desire to produce high-quality, value-adding analytics.
and MLOps solutions.
● Ability to take end-to-end ownership of initiatives, ensuring that adding business value
is always the guiding light.
● An enterprising nature where one can identify problems or opportunities and take
responsibility for the solution and implementation thereof.
● A strong demonstrated desire to learn, upskill and self-improve.
● Strong desire to learn new BI and data science techniques, tools, and methods.