- 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
- 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.
- 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).
- 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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Data Analytics Specialist
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Data Analytics Specialist - Randburg, South Africa - Pillango Placements
Description
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:
The final remuneration package offered by the employer will be determined based on market standards, considering the candidate's qualifications, skills, and level of experience. The employer retains the prerogative to provide a remuneration package that aligns with industry norms and the specific attributes of the selected candidate.