About the Role
We are looking for a Implementation Engineer to join our growing team of Analytic experts. If you are a dynamic leader who wants to work with a team of highly competent professionals in a fast-paced work environment, then this might be the role for you. You will be working with some of the best-in-class Coders, AI/ML Scientist and Business Analytics Consultants in an environment which will encourage you to contribute widely to functional and technological aspects without worrying about conventional job silos to build, implement scalable, standardized cost-effective Decision system platform using Scienaptic’s platform - to support credit decision automation and real-time application decision.
Engage with key stake holders to analyse Business requirements and Use Cases to transform these into Functional specifications, workflow design and configurations into Scienaptic platform
Follow up and escalate gaps, issues and enhancements identified throughout the project
Report progress status to internal stakeholders and/or client for various projects.
Support client activities throughout the implementation of use case life cycle including testing phases
Support test strategy / planning of the end-to-end solution
Create implementation documentation and provide implementation related assistance with other team members as needed
Work with data science and product implementation team to understand overall solution and contribute towards success of the project
Overall, 4-8 years of IT industry experience
Technical Knowledge: Proficient in Native Python, SQL, RDBMS, Jupyter notebook
Experience working with Big data, AWS, Azure, Pyspark will be an added advantage
Experience of API, JSON, JSONata, AWS services will be an added advantage
Strong financial industry experience including business analysis, writing functional specifications, and designing workflows
Good to have in Banking and Financial domain, preferably in implementation through any decision engines such as TRIAD, Powercurve, Origination manager, Blaze etc.
Technical mindset to understand and adapt to overall technical architecture
Process knowledge e.g. managing and tracking requirements, design, delivery etc.
Ability to perform data research and root cause analysis on data issues/discrepancies
Good communication skills including verbal and writing skills