Machine Learning Developer

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 Machine Learning Developer acts as the critical node between our research and our engineering teams. They are experts at productionizing, monitoring, and scaling our advanced quantitative models. 


As a specialized member of the engineering team, you will work closely with our quantitative researchers, data scientists, and software engineers. Your primary responsibility will be improving and productionizing our models. Your secondary responsibility will be to contribute to and support the data science research team. 

  • Work with the data science team to turn research notebooks and models into robust, tested, and scalable production models 
  • Integrate production models into the existing technical infrastructure. This includes dockerization, writing to persistence layers (Mongo DB, Azure Data Lake, MS-SQL), and deploying to on-prem or cloud locations 
  • Augment existing models by proposing technical enhancements, tuning model structure, and performing hyperparameter searches 
  • Work with a small team to design and implement MLOps pipelines for the ongoing monitoring, training, and tracking of deployed models
  • Develop novel machine learning overlays to enhance traditional quantitative models 
  • Propose and test novel ideas for the application of ML in finance and investment management 
  • Summarize and present technical results to technical leadership, with optional opportunities to present to non-technical leadership 

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 3 years of combined experience across: advanced degrees in a relevant field, professional experience, or post-secondary diplomas.
  • You have an undergraduate degree in software eng, comp sci, statistics, or related field 
  • You have proficient numerical programming abilities, comfortable writing and reading code making heavy use of numpy, pandas, scipy, statsmodels, scikit-learn, and tensorflow. 
  •  You never blindly trust a model – you are committed to testing, monitoring, and re-testing
  • You have intermediate programming skills in object-oriented python 
  • You are interested in financial markets, and believe that patient application of the scientific method and quantitative skills will lead to long term results 
  • You have familiarity with, or an interest in learning Docker, Kubernetes, and cloud-based architectures

Previous experience working with financial data or time series data 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