Latest Recruitment at Jubilee Insurance

Job Ref. No.: JLIL147

Role Purpose

• The Data Scientist is responsible for advising the business on the potential of data, to provide new insights into the business’s mission, and through the use of advanced statistical analysis, data mining, and data visualization techniques, to create solutions that enable enhanced business performance.

Main Responsibilities
 Operational:

• Execute ad-hoc data mining and exploratory statistics tasks on large datasets related to the business 'strategies.
• Build econometric and statistical models for various problems inclusive of projections, classification, clustering, pattern analysis, sampling and simulations.
• Build the foundation of state-of-the-art scientific and technical capabilities within the Data Science department in order to support several planned and ongoing data analytics projects.
• Provide forward-thinking recommendations to the business by building in-depth understanding of the problem domain and available business data assets, especially those pertaining to strategic initiatives and value-based programs.
• Generate actionable insights applying advanced statistical techniques, for example, predictive statistical models, segmentation analysis, customer profiling, analysis, survey design, and data mining.

 Corporate Governance (Regulatory and Compliance):

• Participate in project execution to ensure that projects scope is understood, completed on time, to service delivery specifications.
• Adhere to data privacy and security regulations, maintain confidentiality, and promote responsible data practices in compliance with regulatory requirements and industry standards.
• Ensure all assigned policies are ‘Read’ and assigned policy or procedures tests are undertaken and the lowest acceptable score is 90%.

Leadership and Culture:

• Build strong relationships and communications with stakeholders to ensure customer satisfaction.
• Collaborate with data scientists to communicate obstacles and findings to relevant stakeholders in an effort to improve decision making and drive business performance.
• Continually improving ways of working within the team to drive efficient and impactful engagement and accurate delivery of service.

Key Competencies and Skills

• Demonstrate ability and passion for designing and implementing successful data analysis solutions within a business.
• Ability to apply data-mining techniques in practical real-world business issues.
• Skills in the workings of SQL and scripting languages such as Python
• Familiarity with statistical analysis, data visualization, and data cleansing tools and techniques.
• Strong skill in statistical techniques.
• Familiarity in big data and standardizing and A/B testing.

 Academic Qualifications

• Bachelor’s degree in Statistics, Mathematics, Computer Science, Machine Learning, Economics, or any other related quantitative field.

 Professional Qualifications

• Big Data or Data Science certification from recognized institutions

Relevant Experience

• At least 2 years of working experience working with business analysis/informatics and business outcomes research within a fast-paced and complex business setting, preferably working as a data scientist.
• Experience working in probability and statistics, time-series analysis, or econometrics.
• Experience in the use of machine learning methods, for example, linear regression, decision trees.
• Experience as well as in-depth knowledge of the Python/R programming language and Azure Machine Learning Studio.
   

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Job Ref. No.: JLIL146

Role Purpose

• The data engineer will oversee expanding and optimizing of our data architecture and data pipeline with the purpose of improving data analysis and ML workflows. The data engineer will be handling the design and construction of scalable data systems and research new use cases for data acquisition.

Main Responsibilities
 Strategy:

• Design and develop a data estate that is performant, accessible, secure, scalable, maintainable, and extensible. This includes AWS/Azure Data Lake and all other integrating functionalities and layers like ML, Analytics and data science.
• Design and develop and maintain data pipelines including ML pipelines.
• Model EDW entities and ensure all data is complete, accurate, timely, and well documented.
• Work towards the implementation of a true Self-Service analytics platform.
• Implementation of CI/CD practices within the data platform

Operational:

• Follow existing processes and work to improve/identify gaps in these processes.
• Ensure the correct SDLC promotion processes are followed.
• Follow the correct sign-off processes to ensure that only approved releases are deployed into Production.
• Ensure that all AWS/Azure development follows CI/CD processes and is repeatable.

Corporate Governance (Regulatory and Compliance):

• Ensure compliance with regulatory and industry standards, data privacy, security, and governance requirements.
• Ensure that all work follows the best security practices and fully adheres to DPA and other data regulations.
• Ensure that all work follows the correct approval and sign-off process before it is pushed into Production.
• Ensure that all work is documented and if needed, has a runbook in order to guarantee business continuity and support.
• Work with others in the team to keep the Data Dictionary and Ubiquitous Language complete and up to date.

Leadership and Culture:

• Build relationships with members of the data team and the wider business team.
• Work closely and collaboratively with all members of the data team.
• Work closely with and learn from tech and team leads and challenge proposed solutions with your own ideas.

 Key Competencies and Skills

• Experience and knowledge of the SQL query language.
• Understanding of data architecture and data modelling techniques
• Experience with cloud technologies in building and maintaining platforms.
• ETL and ELT experience - both batch and microservices-led.
• Proven experience working with data.

 Academic Qualifications

• Bachelors’ degree in IT or related fields

 Professional Qualifications

• Certification in Azure/GCP/AWS preferred.

Relevant Experience

• Minimum three years’ experience in a data engineer role or similar.
• Experience and knowledge of a coding language such as Python specifically data manipulation