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.
Responsibilities
- 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.
Requirements
- 8+ years’ data analysis experience within an insurance environment
- 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
Additional details
- As an applicant, please verify the legitimacy of this job advert on our company career page.
- 346021306
Zobhira
