What you will do:
Data Analysis & Processing
- Evaluate and clean data sets from various sources (SQL databases, NoSQL databases, graph databases, documents, corpora) to ensure they are ready for AI/ML modeling.
- Proficiency in data preprocessing techniques such as handling missing data, outlier detection, normalization, and transformation to ensure data readiness for modeling.
- Integrate and merge disparate datasets to create unified datasets suitable for AI/ML modeling.
AI/ML and Quantitative Modeling
- Develop custom AI/ML or statistical models tailored to specific use cases in investment management.
- Evaluate, fine-tune, and deploy open-source AI/ML models for various applications in investment management.
- Experience with several of the following frameworks: Pandas, NumPy, SKLearn, XGBoost, PyTorch, TensorFlow, Keras.
Prototyping & Deployment
- Proficiency in prototyping lightweight AI/ML solutions to quickly validate hypotheses and demonstrate feasibility.
- Develop wrapper APIs for model integration and interaction with other systems.
- Integrate AI/ML models with existing systems and databases, ensuring seamless functionality and performance.
Performance Improvement
- Monitor the performance of AI/ML models and make adjustments to improve accuracy and efficiency.
- Identify and design performance metrics for models to monitor, improve, and adjust models to maintain or enhance accuracy, efficiency, and reliability.
Product Discovery
- Collaborate with business stakeholders, particularly Investment and Risk Management teams, to scope out modeling requirements and success metrics.
Research & Innovation
- Stay up-to-date with the latest research and advances in AI/ML and its applications to investment management.
- Apply innovative techniques to a variety of use cases in investment management.
- Commitment to staying updated with the latest research trends, advancements, and best practices in AI/ML relevant to investment management.
- Apply innovative AI/ML techniques and approaches to solve complex challenges and explore new opportunities in investment management.
Collaboration
- Experience working collaboratively with data engineers, software engineers, and teams in investment management and risk management to develop AI/ML solutions.
- Strong interpersonal skills and ability to work effectively in multidisciplinary teams, contributing to shared goals and outcomes.
Communication
- Clear and concise communication skills to articulate complex AI/ML concepts, methodologies, and results to non-technical stakeholders and team members.
- Capability to present findings, insights, and recommendations from AI/ML experiments in a compelling and understandable manner.
Documentation
- Document AI/ML experiments, methodologies, findings, and insights systematically for future reference and knowledge sharing.
Our Technology Stack
- Programming Languages: Python (primary for AI/ML), SQL (data querying), and/or proficiency in some object-oriented language.
- AI/ML Frameworks and Libraries: TensorFlow, PyTorch, Keras, Scikit-learn, XGBoost, Pandas, NumPy.
- Data Storage and Management: SQL Databases (MySQL, PostgreSQL, MS SQL Server, Snowflake) and NoSQL Databases (MongoDB, Cassandra).
- Cloud Platforms and Big Data: AWS (EC2, S3, Lambda, SageMaker, Glue, Athena).
- Containerization, Orchestration, and Development Tools: Docker, Kubernetes, Flask, FastAPI, Django, GitHub, GitHub Actions, MS DevOps,, Jupyter Notebooks, Anaconda, VSCode/PyCharm.
What you bring:
- A master’s or Ph.D. in a quantitative field.
- 9+ years of overall experience including grad school.
- 5+ years of experience in building production-level AI/ML and other quantitative models.
- Strong foundation in statistics, optimization, NLP, and AI/ML algorithms, with a specialization in at least one of the areas.
- Experience in investment management or related financial domains is preferred.
- Proficiency in Python, R, or an object-oriented programming language.
- Familiarity with distributed computing tools and cloud platforms (AWS, Azure, GCP).
- Excellent problem-solving skills and ability to think creatively.
- Strong interpersonal skills and ability to work effectively in a collaborative team environment.
The pay range that the employer reasonably expects to pay for this position is between CA$150.00 and CA$120,000
Our voluntary benefits offering includes medical, dental, vision and retirement benefits.
Applications will be accepted on an ongoing basis.
Tundra Technical Solutions would like to thank you for the interest you have demonstrated in this opportunity. However, only candidates with the required skills will be contacted.
Tundra Technical Solutions is an Equal Opportunity/Affirmative Action Employer. We welcome and encourage diversity in our workplace.
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Tundra Technical Solutions is among North America’s leading providers of Information Technology and Engineering staffing and consulting services. Our success and our clients’ success are built on a foundation of service excellence. Rather than continually trying to sell to new clients and companies and simply filling databases with candidates, we focus on developing stronger relationships and deeper knowledge of our existing clients’ challenges and opportunities.
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