Data Scientist

At Viewpoint, we sit at the intersection of data science and timeless investment philosophies. We integrate core financial and economic principles with advanced quantitative methods to develop end-to-end systematic investment solutions. 

We are looking to add to our data science function, where we develop the next generation of quant strategies. A successful Financial Data Scientist understands the chaos of financial markets through the languages of statistics, probability, and algorithmic coding. They have the drive and skills to discover the patterns and opportunities others miss. 


As a member of the data science function on the research team, you will focus on developing novel techniques to extract information from financial markets and the global economy. You will integrate AI/ML techniques, empirical analysis, and statistical testing with economic theory to create unique insights. 

  • Develop, test, and analyze quantitative financial models using techniques including statistical inference, machine learning, Bayesian inference, deep learning, and stochastic calculus
  • Use numerical programming techniques to solve optimization problems in linear, convex, and non-convex spaces
  • Perform literature reviews from academic and practitioner sources, summarize the findings, and recommend courses of action to leadership. 
  • Write library code suitable for all phases of financial engineering: ingestion, cleaning & indexing, exploratory analysis, feature engineering, and statistical modelling. 
  • Propose novel ideas for the application of ML in finance and investment management. 
  • Develop and publish research results for internal and external consumption. 

We are cloud native and primarily use python in our financial modelling. However, we believe that talented people can learn the necessary skills to work in any environment. 


We aren’t beholden to lists. No one checks every box – if this sounds like you but you miss a few check marks, apply!

  • You have a combined 4 years of experience across: obtaining an advanced degree in data science, statistics, or related field; professional experience; post secondary diplomas. 
  • You have demonstrable skills in linear algebra, statistics, probability, and calculus. 
  • You understand and respect how time series analysis differs from working with tabular or unstructured data. 
  • You don't just build models – you also know how to diagnose them, explain them, and test them for robustness. 
  • You have intermediate development skills in Python, R, or Julia. You can work with libraries such as numpy, pandas, statsmodels, scipy, scikit-learn, and tensorflow. 
  • You love to make beautiful visualizations to tell your data’s story, and have experience using libraries such as matplotlib, ggplot, plotly, d3, or equivalents. 
  • You are comfortable reading and writing mathematical notation. 

Previous experience working with financial data, stochastic systems, and/or time series analysis will be considered an asset. 


  • We believe in a culture of empowerment. You will have direction and autonomy in your work and a consistent feedback cycle of support
  • We invest for the long term, in markets and in our people. You won’t be a commodity, and in exchange we ask for conscientiousness in your work
  • We believe great problem solving takes time and multiple iterations
  • Our passion for financial markets is rivaled only by our passion for working with incredible people


  1. 1
    First round interview: experience and role fit
  2. 2
    Technical Interview
  3. 3
    Final interview: chat with CEO/COO

Please submit your resume with a brief cover letter to Ben Reeves via email at