[SC2 jobs] NAG (Numerical Algorithms Group)

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NAGlogoNAGlogoStudent Placement: Computational Software Engineer

Gain invaluable experience developing technical software in a commercial setting

About the Role

NAG is looking for a Computational Software Engineer to undertake one or more projects within their Development Division. The precise nature of the projects will depend on business needs at the time and on the successful candidate’s skills, but typical examples could be:

  • Porting and testing versions of NAG software to different software or hardware environments.
  • Writing code to implement new algorithms in the NAG Library, along with suitable test programs and documentation.
  • Re-writing code contributed by third-parties to NAG standards and incorporating it into the NAG Library.
  • Using software tools to investigate code coverage of existing test programs.
  • Developing programs which demonstrate the capabilities and advantages of NAG software, to be used by our sales and marketing staff when meeting customers, attending trade shows etc.

For more information please see https://www.nag.com/content/student-placement-computational-software-engineer

[SC2 jobs] CIBC

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Senior Quantitative Developer, Quantitative Solutions – Development

Work Location: Toronto, Canada



Capitals Market Risk Management (CMRM) is led by Senior Executive Vice-President and Chief Risk Officer and is accountable on matters relating to the independent oversight of the management of risks inherent to CIBC’s activities. These risks include but are not limited to ensuring that effective processes are in place for the identification, management, measurement, monitoring and control of operational, reputation and legal, market, credit, investment and liquidity risk, collectively “CIBC Risk”, incurred by CIBC’s retail and wholesale businesses, infrastructure and corporate governance groups.

The Quantitative Solutions (QS) group is responsible for providing quantitative support for model and market data usage across Capital Markets Risk Management, including market risk VaR models used for economic and regulatory capital, and credit PFE models used for counterparty credit management. The group is responsible for methodology, development, calibration of models, market data quality and usage and explaining and troubleshooting model performance. The group is also responsible for tracking and coordinating changes to models across CMRM.

The QS Development group is responsible for developing and prototyping models for use in CMRM, including end-user tools to enhance analysis and reporting capabilities in and relating to the risk systems. The group defines the theory and practice of risk model implementation in Capital Markets Risk, with an eye both to best practices in the field, and to the practical necessities of running large systems with multiple stakeholders. The Development group communicates regularly with stakeholders regarding work in progress, and ensures work schedules are realistic, but ambitious, and that work plans are transparently communicated to stakeholders, including senior management.

Job purpose

The Senior Quantitative Analyst, Quantitative Solutions – Development is a member of a small team of quantitative analysts and developers supporting the CMRM market and credit risk system. The group is in particular responsible for:

  • Developing, testing and ensuring the sound implementation of all risk models for both market and credit risk management in the Trading operation;
  • Implementing risk and data modeling software to allow for ad hoc or ongoing business analysis. The group is expected to work closely with end user stakeholders in this case;
  • Ensuring, jointly with CMRM and QS stakeholders, that the schedule of work is prioritized, maintained and transparently communicated to all involved;
  • Ensuring a high quality of communication occurs;
  • Managing key relationships with related Technology areas, including Treasury and Risk Management Technology (TRMT) and Wholesale Bank Technology (WBT);
  • Helping to establish the strategic context in which the Quantitative Solutions group functions, ensuring this context is informed by market practice and by practical aspects of existing architecture and risk systems implementation.

Key accountabilities

  • Provide rapid development of end-user computing tools to supplement analytics of risk systems, and ad hoc tools for risk quantification.
  • Development support of legacy risk systems, prototyping vendor solutions.
  • As directed, partner with risk quants and other technology groups.
  • Communicate ideas effectively to stakeholders.
  • Ability to support quantitative development in a variety of platforms: legacy in-house analytics, interaction with the vendor systems, ad hoc tools that can be deployed to end users.
  • Meet governance and documentation standards for code changes, ensuring code can be transitioned seamlessly to other developers.
  • Support continuous enhancement of the MRM models for pricing and risk measurement of derivatives and other complex products, market risk, credit risk, and calibration of parameters.
  • Participate as a key member in cross-functional working groups, to implement joint work in support of all accountabilities.

Cross functional relationships

  • The incumbent collaborates with peers and management within Capital Markets Risk Management, WBT, TRMT, Risk Systems, Vendor developers.

Compliance requirements/responsilibities

  • As an employee of CIBC, the incumbent must comply with all applicable CIBC and Line of Business policies, standards, guidelines and controls.

Job dimensions

  • Support enhancements in quantitative risk systems through systems development work, often working independently on projects involving external stakeholders.
  • Primary clients: Risk Managers, Risk Reporting, Technology, QS – Methodology
  • Accountable for Market and Credit Risk within Capital Markets.

Knowledge and skills

  • Graduate degree in an analytic discipline, such as computer science, mathematics, statistics or physics
  • Three years’ experience in quantitative development in risk management, sufficient to formulate and develop valuation, hedging and risk measurement concepts and models or extensive software development experience
  • Strong programming skills and ability to develop in multiple programing and statistical languages (C++/C#, R etc.)
  • Familiarity with Distributed Computing, Data Science discipline, statistical modelling, machine learning and working with large datasets
  • Significant experience with risk technologies, including knowledge of common methodological issues
  • Experience in small to medium-sized projects, likely as a subject matter lead.
  • Analytical/systematic thinker. Takes a well-ordered and logical approach to analyzing problems, organizing work, and planning action.
  • Relationship builder. Develops and maintains strong relationships with internal and external customers/contacts.
  • Results oriented. Strives to achieve high levels of individual and organizational performance.


Accountability, Teamwork & Partnering
Building Trust and Relationships
Results Orientation
Creative/Innovative, Analytic/Systematic, Conceptual and Forward & Strategic Thinking
Impact & Influence
Service Orientation

Working conditions

This role operates within a normal office environment with minimal risk of ill-health or injury. Work pressures caused by tight timelines and quick decisions required on a frequent basis.

The role may require that the employee be available to work non-standard business hours and holidays as assigned by management.

How to Apply

If interested please contact Dejan Kecman at dejan.kecman@cibc.com

[SC2 jobs] Altair Engineering

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Internship Position in Machine Learning

altair_logoJob Description:

We are looking for an intern that will lead a benchmark of machine learning algorithms for engineering applications; specifically related to digital twin and predictive maintenance.

Founded in 1985, Altair is headquartered in Troy Michigan with regional operations throughout 22 countries and provides software and services to over 5,000 corporate clients representing the automotive, aerospace, government and defense, and consumer products verticals. Altair also has a growing client presence in the electronics, architecture engineering and construction, and energy markets.

Altair prides itself on its business culture that enables open, creative thinking, deeply valuing our employees and their individual contributions towards our clients’ success as well as our own each and every day. There is an entrepreneurial spirit that flows and is encouraged throughout our global workforce to develop and gather technology that is relevant to engineering and business – including employing it within our own organization.

In this position, you will be working with a team of engineers, computer scientists and mathematicians that has over 25 years of experience in developing and applying predictive and prescriptive analytics to a variety of applications including but not limited to mobile phones, planes, bikes, consumer products, whitegoods and automobiles.

The outcome of this project will shape Altair’s offerings in emerging domains such as predictive maintenance, digital twin and autonomous vehicles.


Altair headquarter building in Troy, MI; part-time telecommuting is acceptable.


1. Review public datasets and choose a subset to be used for benchmarking.
2. Review available predictive modelling/machine learning tools and identify the ones to include in the benchmark.
3. Become familiar with the predictive modelling/machine learning implementations in Altair such as the ones in HyperStudy.
4. Conduct the benchmark for performance and accuracy
5. Make suggestions for methods and applications.


  • Graduate student in data science or related fields.
  • Bachelor of Science Degree in Mechanical Engineering, Aerospace Engineering, Materials Sciences or related fields.
  • Experience with data analysis and prediction modelling tools and languages such as R, Python, SAS, Matlab, Tableau, MicroSoft Azure.
  • Experience in engineering or scientific work is preferred.
  • Experience with machine learning, predictive and prescriptive modelling methods.
  • Excellent communication skills both written and verbal.
  • Good presentation skills.

Application procedures:

To apply please contactFatma Y. Koçer-Poyraz at fatma@altair.com