Analyste de données – M&V/ Data Analyst - M&V

Trane Italia•Montreal, QC

42d•Hybrid

About The Position

The Data Analyst - M&V will lead the analysis and modelling of building energy consumption data using linear regressions and other models proposed by IPMVP and ASHRAE GUIDELINE 14. This role involves supervising baseline and post-installation data collection, including trend data from building automation systems, field measurements, data loggers, and performance tests. The analyst will use software like Trace 3D+ to create representative models of sites and leverage data to calculate energy savings for individual buildings and portfolios. Key responsibilities include evaluating project performance risk, analyzing savings calculations, interpreting energy consumption data patterns, and reviewing final M&V plans. The position requires generating and reviewing regularly updated savings reports, communicating results to stakeholders, and providing technical assistance for energy management systems, including troubleshooting, diagnostics, and energy savings analysis. The analyst will also maintain project visibility, identify poorly performing projects early on, and collaborate with relevant teams to create performance improvement plans. Furthermore, the role involves developing standard work and systems to improve the quality and efficiency of internal processes, and extracting, manipulating, and presenting results from large quantities of data through various applications.

Requirements

Minimum BSME or equivalent degree in related area of study pertaining to data analysis, modelling, and general modelling: mechanical engineering, building engineering, mathematics, etc.
Knowledge of HVAC principles and basic familiarity with HVAC equipment.
1-2 years' experience with data analysis/modelling and the application of statistical principles.
Familiarity with R and SQL.
Ability to work well under pressure and handle competing priorities.
Excellent communicator.
Comfortable interacting with multiple individuals from various departments to patiently explain results in different ways depending on the stakeholders involved.
Adaptable. Procedures change and it’s important that the candidate be eager and willing to adapt to new/updated procedures and processes as needed.
French-English bilingualism is required.
Full professional proficiency in English in order to support and collaborate with English-speaking clients, colleagues and/or various stakeholders.

Nice To Haves

Proficiency programming in Python preferred.
Prior experience in M&V with IPMVP - ASHRAE GUIDELINE 14 is preferred.
Possession of CEM, EMIT and/or CMVP titles is a strong asset.

Responsibilities

Lead the analysis and modelling of building energy consumption data using linear regressions and other models proposed by IPMVP and ASHRAE GUIDELINE 14.
Supervise baseline and post-installation data collection, including trend data from building automation systems, field measurements, data loggers, and performance tests.
Use software including Trace 3D+ to create representative models of sites (different from the statistical models), and leverage the data provided to calculate savings on individual buildings as well as portfolios.
Evaluate project performance risk, analyze savings calculations, interpret patterns in energy consumption data, and review final M&V plans.
Generate regularly updated savings reports and review those prepared by your peers.
Communicate the results of your calculations to the relevant stakeholders in a timely manner through multiple communication channels.
Provide technical assistance with ongoing review of data from energy management systems, including troubleshooting, diagnostics, and energy savings analysis.
Maintain visibility on projects and identify poorly performing projects early on to the relevant stakeholders through the use of reports and other appropriate channels.
Troubleshoot sites with poor performance and work with relevant teams to create a performance improvement plan.
Develop standard work and systems to improve quality and efficiency of internal processes.
Pull, manipulate, and present results on large quantities of data through various applications, both internally developed and externally available.