The data solution developer will be responsible for all phases of the software development lifecycle for data products. The individual will work with business units and data scientists; to build highly performant and scalable web applications powered by machine learning models.
- Minimum Qualification:Degree
- Experience Level:Mid level
- Experience Length:3 years
- Work with data scientists to integrate machine learning models into web applications
- Design and build APIs for data consumption
- Automate repetitive tasks within the bank
- Produce clean, efficient code based on specifications
- Integrate software components and third-party programs
- Troubleshoot, debug and upgrade existing web applications
- Gather and evaluate user feedback
- Recommend and execute improvements
- Create technical documentation for reference
- Consult with users to refine, test, and debug web applications to meet business needs
- Participate in design meetings.
- Minimum academic qualification – Bachelor’s degree in Computer Science, Information Technology, Information Systems, Statistics, Applied Math, or any other related field.
- 3 - 5 years of experience in web application development
- Experience in financial services will be an added advantage
- To be successful in this role, you will be a team player with a keen eye for detail.
- Familiarity with Agile development methodologies
- Experience with software design and development in a test-driven environment
- Good knowledge of programming languages (e.g.
- Experience with relational databases (e.g MSSQL, Oracle, etc)
- Sound Understanding of data exchange structures (e.g XML, JSON, etc)
- Experience with big data tools such as Hadoop,
- Scala and Spark will be an added advantage
- Ability to learn new languages and technologies
- Excellent communication skills
- Resourcefulness and troubleshooting aptitude
- Attention to details
- Innovative & Open Minded
- Interpersonal skills
- Collaborative skills
- Communication (oral & written)
- Coordination skills
Key Performance Indicators:
- Development of highly performant and available systems
- The efficiency of applications and machine learning models deployed
- Number of manual processes replaced by automation
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