Manager: Actuarial Predictive Analytics and

6 months ago

Pretoria, South Africa Ditshaba Full time

**Qualifications**
- Bachelor’s Degree/Advanced Diploma in Actuarial Science/Mathematics/Statistics/Data Science related qualification.
- Postgraduate in a Financial Management/ an Investment Management/ an Accounting/ a Risk Management related qualification will be an added advantage
- At least 6 (six) professional actuarial exam passes/exemptions will be an added advantage.

At least one Data Science of the following certifications:

- Data Science Certificate, CCP Data Engineer or SAS Academy for Data Science,
- Certified Analytics Professional, Dell EMC Data Science Professional Certification Program,
- SAS Advanced Analytics Professional Certification,
- IBM Data Science Professional Certificate,
- Microsoft Azure Data Scientist Associate Certificate,
- AWS Certified Data Analytics,
- Certified Analytics Professional, Harvard/EdX Professional Certificate in Data Science, DASCA: Senior Data Scientist,
- Coursera: Data Science Specialization.

Experience
- Relevant 6-8 years’ experience in an actuarial data science related environment of which 2 years must have been in management/supervisory level/area of expertise.
- Experience in SAS (Base, Enterprise Guide, and Enterprise Miner), Python or R
- Experience in building and implementation of supervised and unsupervised Machine Learning Algorithms to solve meaningful business problems.
- Some experience with Python/Microsoft Machine Learning and tools available within the machine learning ecosystem (i.e. NumPy, pandas, matplotlib, SciPy stack) and working in Jupyter notebooks.
- Some experience in operationalizing data science solutions or similar product development.

Competencies Behavioural:

- Resilience
- Communication
- Working with People
- Network and Alliances
- Planning, Organising and Coordinating
- Employee Engagement
- Personal Mastery
- Judgement and Decision Making
- Ethics and Values

Client Service Orientation Managerial:

- Change management
- Coaching and mentoring
- Conflict management
- Critical and innovative thinking
- Direction setting
- Facilitation and Presentation Skills
- People management
- Policy conceptualisation and formulation
- Risk Management
- Programme/project management
- Service Delivery Innovation
- Stakeholder development and relations

Reporting Technical:

- Excellent verbal and written communication skills.
- Strong Microsoft Excel, Access and MS Word skills.
- Complex problem identification, solving and decision making.
- Sound actuarial judgment.
- Strong technical background in data analytics and modelling.
- Strong planning and time management of both own and direct team's work
- Strong focus on executing plans and delivering results.
- Pro-active approach and keen to take ownership of work.
- Independent and creative in analysing business results, develop appropriate solutions or alternatives to problems and effectively communicating related issues and results to management.
- Result oriented and ability to work under pressure.
- Work well in team-oriented, collaborative environment.
- Excellent analytical, problem solving & data manipulation skills.
- External force and industry knowledge
- Understanding of Actuarial reserving and valuations
- Understanding of Statistical and financial analysis
- Understanding of Forecasting and projections
- Knowledge and understanding of the Data Science Development Cycle: business understanding, data profiling, feature derivation and selection, data modelling, model evaluation, production, monitoring.
- Outstanding problem solving and analytical skills.
- The ability to build, analyse and interpret numerical and non-numerical data to determine potential statistical inferences to inform business and clinical decisions.
- Ability to clean and unify messy and complex data sets for easy access and analysis.
- Ability to conceptualize and frame a problem, develop hypothesis and identify objective measures to estimate accuracy of machine learning/statistical processes and perform testing and validation with careful experiments.
- Understand leading edge technologies and best practice around Big Data platforms and distributed data processing

Policy review and implementation
- Contribute to the development and implementation of departmental policy, procedures and processes.
- Keep up to date with effective policy and practice execution strategies.
- Review and update all policies relating to data science

Predictive analytics and modelling
- Work with data to develop our machine learning and predictive analytics solutions in order create or improve i) fraud detection, ii) liability projections, iii) fuel levy projections models to optimize risk management for the Asset and Fund Management Department.
- Use analytical, statistical and programming skills to collect, analyse and interpret large data sets in order to provide insights and data-driven solutions to solve difficult and strategic business challenges.
- Work with data scientists to develop our machine learning and pr

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