Data Scientist - Insights
Minimum requirements:
- Matric / Grade 12 / National Senior Certificate
- Advanced Diplomas / National 1st Degrees
- Post Graduate Degree Computer Science, Econometrics, Mathematical Statistics, Actuary Science (ideal)
- SAS Data Scientist certification, Microsoft Data Scientist, IBM data engineer (ideal)
- Post graduate degree in computer science, statistics, or operations research or related technical discipline.
- 4-6 years experience in a statistical and/or data science role.
- Deep knowledge of machine learning, statistics, optimization or related field.
- Experience with R, Python, Matlab is required, programming in C, C++, Java.
- Experience working with large data sets, simulation/ optimization and distributed computing tools (Map/Reduce, Hadoop, Hive, Spark, Gurobi, Arena, etc.)
- Excellent written and verbal communication skills along with strong desire to work in cross functional teams.
- Attitude to thrive in a fun, fast-paced start-up like environment
Technical / Professional Knowledge:
- Analysing situations or data that requires an in depth evaluation of multiple factors
- Data Mining
- Data Warehousing
- Financial modelling and analytics
- Research and analytics
- Strategy planning and execution
Responsibilities:
- Develop best-in-class statistical models and algorithms
- Conducts advanced statistical analysis
- Provide actionable insights, identify trends, and measure performance
- Create value out of enterprise wide data
- Provide insights to BI and BA to further exploit and present their models
- Provide strategic direction ito data information received
- Apply advanced analytical techniques such as machine learning and artificial intelligence in order to derive business value.
- Conduct data discovery for inclusion in models.
- Collaborate with key stakeholders to obtain business acumen and intellectual property
- Keep abreast with latest tools and techniques
- Understands business problems and designs end-to-end analytics use cases
- Collaborates with model developers to implement and deploy scalable solutions
- Develop complex models and algorithms that drive innovation throughout the organization.
- Ensure improvement of on-time performance and network planning
- Provide thought leadership by researching best practices, conducting experiments, and collaborating with industry leaders.
- Work with large data sets, simulation/ optimization and distributed computing tools (Map/Reduce, Hadoop, Hive, Spark, Gurobi, Arena, etc.)
- Ensure understanding of pros and cons of different analytics approaches for problem type.
- Implements more advanced algorithms, e.g., complex descriptive.
- Ensure Quality controls of own work and those of junior scientists.
- Understand current state of analytics more broadly and apply techniques from across industries.
- Map problems and quantify the impact of proposed measures.
- Develop and prioritise use case roadmaps
- Support the achievement of the business strategy, objectives and values by reviewing company and Business Unit Plan and ensuring delivered systems, process, services and solutions are aligned.
- Improve personal capability and stay abreast of developments in field of expertise by identifying training courses and career progression for self through input and feedback from managers.
- Ensure personal growth and enable effectiveness in performance of roles and responsibilities by ensuring all learning activities are completed, experience practiced and certifications obtained and/or maintained within specified time frames.
- Enable skilling and required corrective action to take place by sharing knowledge and industry trends with team and stakeholders during formal and informal interaction.
- Obtain buy-in for developing new and/or enhanced processes (e.g. operational processes) that will improve the functioning of stakeholders' businesses by highlighting benefits in support of the implementation of recommendation