Description
You will be working on a flexible hybrid schedule as part of Fidelity’s dynamic working arrangement.
Who We Are
At Fidelity, we’ve been helping Canadian investors build better financial futures for over 35 years. We offer individuals and institutions a range of trusted investment portfolios and services - and we’re constantly seeking to find new and better ways to help our clients. As a privately owned company, we boldly embrace innovation in all areas as we continue to grow our business into the future.
Working with us means you’ll be part of a diverse and dedicated group of people who make a real difference for our clients and communities every day. You’ll have a wide range of opportunities to grow and develop your career in an inclusive environment where you’ll feel valued and supported to be your best - both personally and professionally.
What You’ll Do:
As an ML Analyst, you will be collaborating with an interdisciplinary team that leverages large datasets using highly scalable computational resources to deliver end-to-end AI/ML based solutions. You will be responsible for conducting exploratory data analysis, data pre-processing and transformation, developing ML algorithms, and assisting with deployment using both on-premise and cloud-based platforms.
Develop machine learning-based software solutions using open source and proprietary software systems
Conduct applied research to identify and understand different algorithms and methods for use case development
Collaborate effectively within agile scrum sessions alongside the Emerging Technology, IS ML Ops teams and business stakeholders to develop and implement high impact business solutions
Rapid prototyping of new algorithms/approaches and conducting comparisons with existing algorithms and baselines
Models with unsatisfactory baseline results are constantly revisited to seek improvement - particularly those with a high degree of potential business impact
Assist the IS Infrastructure and IS ML Ops teams in designing customized ML environments as needed
Support projects through the documentation, monitoring and version control of models
What We’re Looking For:
A completed Master’s Degree in Computer Science, Statistics, Software engineering or other STEM discipline or equivalent working experience
Experience with data collection, data annotation, and active learning
Solid theoretical grounding in core machine learning concepts and techniques
2+ years of experience within a data science, artificial intelligence and/or applied machine learning position
1+ year of experience with cloud computing is an asset
1+ year of experience building production machine learning models, and deploying them to solve inference challenges at scale is an asset
Strong understanding of machine learning approaches: predictive modelling, supervised and unsupervised learning, genAI, computer vision, etc.
AWS Certified Machine Learning and AWS Certified Data Analytics AWS Certified Data Analytics is an asset
Investment Funds in Canada and/or Canadian Securities Course (CSI) is an asset
1–2 years of experience working with Snowflake, including strong SQL skills
Experience using Git for version control (e.g., Git Hub), including branching, pull requests, and code reviews
The Skills You Bring:
Strong communication skills and the ability to work with diverse stakeholders in team environment
Ability to adapt quickly in the face of change using excellent problem-solving skills and creativity
Familiarity with popular Python-based AI/ML libraries (e.g., scikit-learn, PyTorch, pandas, Num Py, matplotlib) and associated workflows
Experience with deployment of machine learning model pipelines using AWS (e.g. Sage Maker)
Familiarity with containerization of ML models (Dockers and Kubernetes)
SQL skills for querying relational databases (e.g. Oracle, SQL Server, DB2, MySQL)
Demonstrated proficiency with deep learning, ensemble-based methods, NLP, time series analysis, and optimization techniques
Current work authorization for Canada is required for all openings.
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