Nishish Doshi

Experienced professional with a quantitative finance background, good skills in risk analytics, statistical and predictive modelling, and object-oriented programming, as well as a track record of developing/implementing practical software solutions in the areas of process automation and technical analytics, actively seeks a role as a Python Developer, with responsibility for developing highly automated as well as technically robust solutions, capable of being easily executed in different environments through proper use of environment variables.

Such a solution could involve: Using Statistical, Regression, or Time Series analysis; Implementation of a variety of Machine Learning algorithms (Supervised vs. Unsupervised); Using Linear Programming & Non-Linear Programming techniques, via Python’s PuLP & CVXOPT libraries, to find solutions to constrained portfolio optimisation problems; Market Risk, Stress Testing, or Buy-Side Portfolio Risk Analytics.

Moore Europe Capital Management, London

Python Developer - IT Development (Contract)

Jun 2023 – Present

• Used Highcharts visualisation tool, as well as a React.js based data grids tool, for the rendition of highly customised timeseries graphs and tables onto a frontend UI screen, with real-time updates. Each of these myriad, JavaScript-driven charting and data grid tools, are backend-supported by Python scripts and carefully structured grid functions, that I would need to have coded up, based on detailed user requirements as communicated via either Jiras, or face-to-face meetings
• Developed a dynamic search functionality app, employing Python and Elasticsearch (incl. Elasticsearch DSL) as its backend, enabling end-users from the Economics Research Team to easily find, in near real-time, all instances of previously saved reports/commentaries containing either a searched keyword(s), or even a target phrase
• Extended existing, and created new as needed, Python utility or helper functions, as a means to better organising, simplifying, and maintaining the codebase. For instance, datahelpers.py, datehelpers.py, etc.
• Responsible for scripting ad-hoc tools for timeseries analysis, including, at times, on a RAD or prototyping basis. Also contributed to certain aspects of an ongoing project to validate, and thereafter incorporate, certain advanced timeseries algorithms offered within the NeuralProphet Python library

MSc (Financial Engineering)