Curriculum Vitae

Louis Becker

Finance professional with strong data and modelling skills. Seven years’ experience working with data, statistical modelling and software development of which the last five years have been rooted in economic and investments analysis in the finance industry. Passionate about technical excellence and best practice with strong preference for Python or R.


July 2018 - Present

Prescient logo.

Head of Analytics (October 2023 - Present)

My role as Head of Analytics ecompasses the dual purpose of overseeing data infrastructure and generating data-driven insights. This role evolved from within the investment team to extended responsibilities across the business. I oversee the data engineering function, data infrastructure, data stack development and any additional fullstack development that happens in-house. Furthermore my role is responsible for ehancing the data culture across the business and maintaining a high standard for data-driven insights.

Practical Exposure:

  • Data: Data infrastructure, data strategy formulation, data governance, data engineering
  • Analytics: Statistical modelling, predictive analytics, financial machine learning, client segmentation, econometric research, real-time analytics, self-service analytics.
  • Tools: Python, R, Rstudio Server, SQL, Docker, JavaScript, HTML, FastAPI, Flask, Shiny, Git, Gitlab CI/CD, React, Next.js.
  • Supervision: Oversight and hands-on with development of Prescient’s PRIME decision making platform, Prescient’s in-house R and Python libraries.
  • Development: Spearhead the full stack development of Prescient Insights, a customer-facing digital platform and sales aid. Start development of Prescient’s in-house portfolio management system.

Technical Lead (July 2022 - September 2023)

As Technical lead in Prescient Investment Management’s data science team, I help manage a team of quantitative analysts, data engineers and data scientists. My role merges data science and finance to produce models, insights and software infrastructure that supports investment decision making processes.

Practical Exposure:

  • Models: Prescient Economic Indicator - nowcast of Real GDP, Natural Rate of Interest Estimate, Multi Asset team systematic investment process.
  • Econometric modelling, financial machine learning, machine learning devops, data warehousing.
  • Python, R, Rstudio Server (set up and maintain) SQL, JavaScript, HTML, FastAPI, Flask, Shiny, Git, Gitlab CI/CD.
  • Overseeing and hands on with development of Prescient’s investment decision making platform as well as in-house R and Python modules supporting analytics.

Quantitative Analyst (July 2018 - July 2022)

My role as a quantitative analyst in the multi asset team revolved around economic research and developing a software platform that investment processes for all our fund strategies. I built the the first iteration of the systematic multi asset investment process. This platform enabled us to generate our investment views, trade towards them and show clients exactly how we think and how we positioned our portfolios on a daily basis.

Practical Exposure:

  • Constructed the Multi Asset Investment Portal all the way from data pipeline to front end. Also built most of the analytics capabilities for this platform.
  • Played a crucial role in designing and implementing a transparent systematic investment process.
  • Econometric and financial modelling, data visualisation, developing scalable investment decision making structures.
  • Advanced automated web front end and computational implementations with R, setting up and managing SQL databases, creating and maintaining automated data pipelines and creating and evaluating model portfolios and data-based decision processes.

April 2017 - July 2018

Eight20 logo.

Data Analyst

My role at Eighty20 Consulting was focused on the FMCG industry where the team I was apart of consulted for a major South African retailer on their loyalty program. We provided services in the form of personalisation, customer insights and analytics.

Practical Exposure:

  • Automated bash and SQL infrastructure tailored to extract, transform and load retail transaction data. I set up an internal database to handle more 1 billion rows of data to support our analytics processes.
  • One of the deliverables to the client was personalised voucher metadata for their customer base. Our process supported automated delivery of customer voucher data from our personalisation partners to our client on a strict two-week cycle.
  • Linux commandline (bash), git, SQL, R, data pipelines and setting up analytics dashboards.


CFA Level I Badge.

CFA Level II Badge.

CFA Institute | CFA Level III Candidate

Stellenbosch University logo

Stellenbosch University | MCom (Economics) | March 2017
Business Cycles: Is the Concept of a Recovery Phase Applicable Internationally?

Stellenbosch University | BComHons (Economics) | December 2015
Macroprudential Policy and Bank Capital Regulation

Stellenbosch University | BComm (Economic Sciences) | December 2013


R Package: pimR | Creator and Maintainer
Prescient Investment Management’s in-house analytics R package for investments and quantitative processes.

Python Library: ppym | Contributor
The PIM Python Module (ppym) is Prescient Investment Management’s in-house analytics Python library for investments and quantitative processes.

PRIME Portal | Maintainer
The Prescient Research and Investment Management Engine is Prescient Investment Management’s research and investment decision making web platform.

Prescient Portfolio Management System | Co-Creator and Maintainer
Being developed to cater for Prescient’s bespoke analytics and implementation requirements.

Personal Budget and Expense Tracker | Creator and Maintainer
A web app from the ground up that automatically tracks my expenses and budgets across multiple accounts. Hoping to expand to a fully automated one-stop shop for my finances.

This website.

See the PDF version of my CV here