Data Analytics Specialist

6 months ago

Johannesburg, South Africa Pillango Placements Full time

**Gauteng**, JHB - North**

**R 79000 - R 81000 Monthly Cost To Company**

As a Data Analytics Specialist, you will be at the forefront of employing leading analytical methods and technologies, ensuring that you're always working with cutting-edge tools and approaches to solve complex problems.

**The purpose of the position is**:

- To contribute excitedly and passionately to our client's 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 prioritised 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.

**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 delivering small to large scale analytics, data science and business intelligence projects which require extensive collaboration across multiple teams.
- Minimum two years experience required. Experience in the Health Tech sector is advantageous
- 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

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