Accountable for designing and implementing data-driven solutions that contribute to business value by leveraging statistical models, machine learning algorithms, data mining,
and advanced visualization techniques
Requirements
- 8+ years’ data analysis experience within an insurance workplace
- Extensive experience with at least one programming language (e.g.
Python), business analytics software (e.g. SAS) statistical package (e.g. R)
- Experience in database language (e.g. SQL)
- Deep theoretical understanding of statistical methods and machine
learning techniques
- Understanding of Artificial Intelligence solutions and techniques
- Ability to apply statistical methods and machine learning
techniques to solve business problems
- Formulating business problems to enable statistical modelling
- Selecting the right statistical tools and techniques for the job
- Experience translating statistical findings into business
recommendations
Duties and Responsibilities
Key Accountabilities/Kras/Kpis
- Identify and develop Predictive and Prescriptive Models to enable
better decision making of business.
- Identify, understand and interpret data structures across various
databases within the business to facilitate data analysis and continuous monitoring activities.
- Delve into insights in data and processes to help improve the business.
- Contribute to the development of differentiated; superior solutions
that meet stakeholder and business requirements through analysis; business requirements gathering and designs validation.
- Ensure product and/or solution design is congruent with the required
business specifications through meeting stakeholder requirements timeously.
- Enable the realization of the financial business benefits accruing
including minimization of operational costs by ensuring that solutions are implemented effectively.
- Model and frame business scenarios that are meaningful and which
impact on critical business processes and/or decisions.
- Participate and/or lead discovery processes with business stakeholders
to identify problems and opportunities that may be addressed with statistical modelling or machine learning.
- Collaborate with business to define approach to resolution of key
business problems or development of new business strategies.
- Contribute to the business by highlighting possible opportunities for
process improvement and business value creation.
- Identify and develop the hypothesis testing framework and modelling
approach to address the business requirements.
- Identify available and relevant data, potentially leveraging new data
collection processes such as social media.
- Make strategic recommendations on data collection and experimental
design incorporating business requirements and knowledge of best practices.
- Prepare the data for analysis and modelling, which includes data
cleaning, standardization, transformation, dimension reduction and feature engineering.
- Identify and train suitable models/algorithms to discover patterns and
make predictions.
- Extend existing code and develop custom code to implement statistical
models,
machine learning algorithms and data mining techniques for large datasets in a computationally efficient manner
- Compare model performance, select the best algorithm for the job
and be able to motivate this choice in a non-technical manner.
- Interpret results and translate findings into clear and actionable
insights that can be easily validated with the project sponsor.
- Communicate findings to business with various skill levels and in
various roles, presenting trends, correlations and patterns found in complicated datasets in a manner that clearly and concisely conveys meaningful insights.
- Assist business users in the use of the models and interpretation of
model output.
- Assist with monitoring and reporting on model accuracy after it has
been embedded in operations
- Provide authoritative, expertise and advice to clients and stakeholders.
- Build and maintain relationships with clients and internal and external
stakeholders.
- Contribute to the process of negotiating objective and realistic service
level agreements, monitor appropriateness and recommend adjustments.
- Define service practices which build rewarding relationships,
encourage innovation and allow others to provide exceptional client service.
- Deliver on service level agreements made with clients and internal and
external stakeholders to ensure that client expectations are met.
- Make recommendations to improve client service and fair treatment
of clients within area of responsibility.
- Participating in and contributing to a culture which builds rewarding
relationships, facilitates feedback and provides exceptional client service. As an applicant, please verify the legitimacy of this job advert on our company career page.
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