Reporting to the engineer Manager - data and working closely with CIO he/she will focus on designing and developing the key frameworks (service engines, API backed business functions) for business process execution as well as work in Data science projects (planning optimization, pricing/scheduling optimization) and driving the industrialization of the python-based software engineering /development processes.
Will be working with the rest of the data analyst team to deliver data science related projects, designing re-usable solutions
Also create the development and design standards for Python eco system, tools and library selection, packaging, build and deployment, CI/CD processes for Python based deliveries.
The role will involve designing and developing risk and trading functionality that can cover MtM calculations, VaR and shocking, PnL calculation, Position reporting and Trade pricing.
The role will also work with rest of technology organisation to improve the SDLC rigor including automated testing, automated build and deployment, design and coding best practices.
Be proactive in active engagement to resolve issues, collaborate with rest of the development organisation to deliver the technology strategy defined by CIO
Be the leader for Python development in Targray and drive the industrializing the Python engineering processes.
Requirements
Bachelor s degree in Computer science with good knowledge in data science topics (supervised/unsupervised ML, Deep learning topics)
10 yrs in software development and 6 yrs solid hands-on experience in Python development.
Strong experience in python frameworks like numpy, pandas, scipy, machine learning and AI libraries, using Python REST and Web Socket APIs in actual real-life projects.
Good experience and knowledge in working in data science projects and deliverables
Worked in Agile delivery methodologies and familiar with agile ceremonies.
Detailed knowledge and experience in design patterns spanning all layers of an application architecture (mid-tier, business logic layer, integration and data layer) .
Good understanding of the CPython interpreter implementation, operating systems infrastructure is advantageous in resolving performance, concurrency issues.
Experience in using unit, component and integration testing with pytest scripting as part of development process, using continuous integration (Jenkins,, Axure DevOps) and using build tools like setuptools and anaconda is must.
Experience in working in financial services, Trading and risk domain either in a enterprise or a software product company is definitely advantageous.
Ability to instrument code, monitor application execution, identify issues and solving them objectively and performance engineering are key needs.
Good experience in using Linux/ Windows OS and accessing/working with cloud IaaS services (hosted VMs) as well as containerized solutions like docker/ Kubernetes
Knowledge in SQL and NoSQL database architectures, writing performant SQL and MongoDB queries and understanding and appreciation of how databases work and utilizing efficient ORM technologies /or alternate efficient data access tools is very important.