Reference Code: CO57210441-01
- Documents and mentors team members in guidelines and standards, ensuring process alignment, shares technical expertise,
provides training, performs code reviews, directs the execution of their tasks, and provides feedback on their technical
performance
- Partners with D&T and business stakeholders to develop ML and AI policies and strategies
- Delivers formal presentations to internal business stakeholders at various levels including executives
Qualifications:
- A four year degree in Computer Science, Data Science, Statistics, Artificial Intelligence, Applied Mathematics, or a related
quantitative field from a university of recognized standing with a minimum of five years general IT experience, including three
years of directly applicable Data & Analytics programming experience launching, planning, and executing data science
projects, including statistical analysis, data engineering, and data visualization
Or
- A two year diploma in Data Science, Statistics, Artificial Intelligence, or a related quantitative field with a minimum of seven
years general IT experience, including three years of directly applicable Data & Analytics programming experience launching,
planning, and executing data science projects, including statistical analysis, data engineering, and data visualization
Or
- Alternate experience and education in equivalent areas such as economics, engineering, or physics is acceptable; experience
in more than one area is strongly preferred
- A specialization in ML, AI, cognitive science or data science is preferred
- Microsoft and/or Databricks certifications in AI and ML preferred
- Fluency in multiple programming languages and statistical analysis tools such as Python, Jupyter Notebook, C++, JavaScript,
R, Scala, SAS, Excel, SQL, MATLAB, SPSS
- Experience with relational database programming languages including SQL and PL/SQL as well as nonrelational databases
such as NoSQL/Hadoop-oriented databases including MongoDB, Cassandra, etc.
- Knowledge of distributed data/computing tools such as Spark, MapReduce, Hadoop, Hive, or Kafka
- Experience working across multiple deployment environments including cloud, on-premises, and hybrid, and multiple
operating systems and containerization techniques such as Docker, Kubernetes, Azure, etc.
- Strong understanding of AI domains such as ML, Generative AI, Optimization, Graphs, and Simulation, and their potential
roles in solving business problems such as prediction/forecasting, planning, computer vision, recommendation, natural
language processing, content generation, and knowledge discovery.
- Experience in one or more of the following commercial/open-source data discovery/analysis platforms: RStudio, Spark,
KNIME, RapidMiner, Alteryx, Dataiku, H2O, SAS Enterprise Miner (SAS EM) and/or SAS Visual Data Mining and Machine
Learning, Microsoft AzureML, Databricks, IBM Watson Studio or SPSS Modeler, Amazon SageMaker, Google Cloud ML, SAP
Predictive Analytics
- Experience in statistical and data mining techniques such as generalized linear model (GLM)/regression, random forest,
boosting, trees, text mining, hierarchical clustering, deep learning, convolutional neural network (CNN), recurrent neural
network (RNN), T-distributed Stochastic Neighbor Embedding (t-SNE), graph analysis, etc.
- Experience in applying DevOps/MLOps methods to the construction of ML and data science pipelines
- Knowledge of Responsible AI with demonstrated experience aligning to Responsible AI best practices
- Understanding of Data Privacy regulations and best practices
- Experience in DevOps and Agile (Scrum/Kanban), preferred
- Willingness and ability to learn new technologies on the job
- Ability to communicate complex projects, models, and results to a diverse audiences with a wide range of technical and
non-technical understanding
- Ability to work in diverse, cross-functional teams in a dynamic business environment
- Good presentation skills, including storytelling and other techniques to guide and inspire
- Ability to create relationships quickly and strengthen relationships confidently
- Demonstrated ability to be the technical lead on multiple projects or activities with competing priorities
Salary Range
Starting salary will be commensurate with qualifications and experience. The range for the classification is $47.22-$65.19 Hourly,
$90,484.68-$124,925.58 Annually.
Apply Now!
Ready to join a team that energizes Manitoba and puts safety, innovation, and inclusion at the heart of everything we do? Visit
www.hydro.mb.ca/careers to learn more about this position and to apply online.
Application deadline: JULY 21, 2026.
We appreciate your interest in Manitoba Hydro and thank all applicants. Only those selected for the next stage of the selection
