Support quantitative risk management projects within Enterprise Risk Management, applying advanced analytics, modeling, and emerging technologies to enhance risk oversight and decision-making.
Compensation
Graduate Interns are paid at a set, non-negotiable hourly rate. The hourly rate for this role is $40/hr.
Responsibilities
Execute quantitative and analytical projects ensuring timely delivery and effective scope management
Develop, evaluate, and utilize quantitative models and analytical tools for market, credit, operational, and emerging risks
Collaborate with risk, business, and technology teams to solve complex problems and drive data‑driven decision‑making
Support model development, validation, monitoring, and evaluation across various risk disciplines
Apply programming, data analysis, and automation techniques to improve efficiency and enhance quantitative processes
Requirements
Graduate degree in Data Analytics, Computer Science, Applied Mathematics, Statistics, Financial Engineering, Econometrics, Quantitative Finance, Artificial Intelligence, Machine Learning, Economics, or a related quantitative field
Senior AI Engineer responsible for developing and deploying generative AI, NLP, vision, and ASR models for enterprise applications.
Compensation
Hiring Range: $169,800 - $233,500 - for Primary Location of USA - CA - Palo Alto
Responsibilities
Evaluate, adapt, and develop new state of the art language and/or multimodal foundation models for enterprise applications
Perform thorough empirical analysis of the approach and write production ready code
Develop, modify and fine-tune ML/NLP and pre-trained enterprise-grade large language models (LLMs) and multi-modal models
Ensure the developed models seamlessly integrate with other tools and company products and are aligned with the feedback that will be generated from enterprise customers
Specify guidelines and design annotation processes for data; collaborate with data team on data preprocessing, consumption, and automated/manual annotations
Requirements
Master’s degree in Computer Science, Engineering, or related fields
Bachelor’s degree in Computer Science, Engineering or related experience
Quantitative Analyst co‑op/internship focused on data analytics, modeling, and machine learning within BMO’s financial services.
Compensation
$65,000.00 - $140,000.00
Responsibilities
Develop and leverage APIs to extract, integrate, and automate data workflows
Create data visualizations, reports, and interactive dashboards
Apply Bayesian statistics and machine learning techniques to real‑world problems
Design and construct new processes for modeling data
Develop predictive models and machine learning algorithms
Requirements
Master's degree or PhD in Quantitative Finance, Financial Engineering, Statistics, Mathematics, Computer Science, Data Science, Economics, or related quantitative discipline
Nice to have: machine learning in financial services
Nice to have: cloud‑based analytics platforms
Nice to have: advanced quantitative research methods
Compensation is competitive for the sustainability sector.
Responsibilities
Identify, design, and drive interventions that improve outcomes for smallholder farmers and their communities
Research, analyze, and quantify potential solutions to sustainability challenges
Assess and develop candidate interventions and ideas across precision agriculture, sustainable livelihoods, carbon sequestration, microfinance, and related areas
Lead the design, launch, and management of programs—piloting, partnering, monitoring, evaluating, and scaling what works
Spend substantial time at origin in smallholder communities across Sub‑Saharan Africa, Latin America, or Asia
Compensation for this role is based upon experience, qualifications, location, and education and typically ranges from $140,000 to $160,000.
Responsibilities
Develop and implement statistical, predictive, optimization, machine learning, and AI solutions
Drive data science projects from discovery to deployment
Define scope, identify risks and dependencies
Build, validate, and evaluate predictive and statistical models
Develop analytical and machine learning solutions with production use in mind
Requirements
Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering or a related quantitative field, or equivalent professional experience
Nice to have: Experience with Databricks, Spark/PySpark, MLflow
Nice to have: Familiarity with modern analytics engineering and development practices
Nice to have: Experience building analytical applications or internal data products using tools such as Streamlit
Nice to have: Experience with cloud platforms such as AWS or Azure
Build and scale AI tooling systems that enable Zipline’s autonomy teams to visualize, annotate, debug, and extract signals from real-world delivery vehicles.
Compensation
The starting cash range for this role is $180,000 - $250,000.
Responsibilities
Build sophisticated, multimodal data triage and visualization interfaces for Zipline’s data pipelines
Build scalable backend APIs and real-time data pipelines for querying, filtering, and aggregating large datasets
Design database schemas, indexes, and query strategies that keep search and analysis fast at scale
Partner with autonomy, service, maintenance, and operations teams to improve workflows and build tools for development, troubleshooting, and fleet health
Responsible for deploying, configuring, and onboarding customers onto proprietary software solutions, serving as the technical lead during post‑sale implementation.
Locations (3)
Karachi, Sindh, Pakistan
Lahore, Punjab, Pakistan
Islamabad, Pakistan
Responsibilities
Serve as primary technical point of contact for customers during implementation lifecycle
Communicate with customers via meetings, calls, and written correspondence
Create and execute detailed implementation project plans
Lead onboarding and kickoff calls
Configure proprietary software and add‑ons
Requirements
Nice to have: SQL SELECT statements, joins, filtering
Nice to have: Enterprise or SaaS software implementation
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