Calgary Jobs ⇝ Data Scientist at MEG Energy - May-2022

Job Posting End Date: Position Type: Employee Position Sub Type: Permanent Full Time Work Location: Calgary, AB Shift: Office Hours (Canada) ____________________________________________________ Join us … MEG is seeking an enthusiastic individual who loves solving problems. As a Data Scientist and key member on our team you will to perform statistical analysis and build/maintain machine learning predictive model applications within the business to help improve decisions and develop solutions to challenges we face. you will work closely with engineers, IT professionals, and business domain experts touching all areas of MEG to learn and understand the business and provide solutions to real world problems. Your day-to-day:

• You will work in a fast-paced environment partnering with multi-disciplinary teams to support MEG's Digital Innovation goals as a Data Scientist or Machine Learning Engineer within the company's Digital Team.
• You will work closely with key stakeholders across the business helping to solve business problems utilizing statistics and data science.
• You will build and maintain predictive applications, models and automations which are solving business problems. Areas may include anomaly detection for predictive failure, augmented decision making through classification models, or virtual flow metering using regression based models.
• As a member of MEG's Digital Team you will be a part of building MEG's skills in Data Science and will be a key contributor on the company's digital transformation journey.
• Proactively identify and champion projects that solve complex problems across multiple domains
• Design and implement end-to-end data pipelines: work closely with stakeholders to build models, tables or schemas that support business processes
• Apply specialized skills and fundamental data science methods (e.g. experimental design, recommender systems and machine learning when needed) to inform improvements to our business
• Build actionable KPIs, production-quality dashboards, informative deep dives, and scalable data products
• Influence leadership to drive more data-informed decisions
• Define and advance best practices within data science and product teams

What you will bring to MEG:

• Bachelor's degree or higher or in Physics, Mathematics, Engineering or Computer Science.
• A minimum of 5 years previous experience in Data Science is required.
• Experience in the Oil & Gas industry considered and asset but not required.
• Experience in industrial processes and data historians (PI), DCS systems and controls considered an asset.
• Demonstrated ability to translate analytical insights into clear recommendations and effectively communicate them to technical and non-technical stakeholders
• Experience in quantitative analysis relating to engineering or other technical problems.
• Proficiency in Python, SQL and common ML libraries (Scikit Learn, Tensorflow, Keras, PyTorch, etc) is required with a focus on data science skills.
• Experience with cloud-based machine learning pipelines (Azure, AWS) or open-source on-prem (CRON, Flask/Django, Gunicorn, etc) solutions.
• A deep understanding of statistics, predictive modeling, and machine learning as they relate to technical problem solving.
• Experience delivering business impact through analysis and data products
• Previous development and deployment of production code for machine learning models.
• Demonstrate enthusiasm and discipline while being able to take ownership, make timely decisions and communicate outcomes.
• Strong team player / excellent interpersonal skills.
• Able to effectively coordinate concurrent activities involving multiple individuals.

#LI-POST __________________________________________________ Be Part of our Team! There are many reasons to work at MEG, including:

• Safety is foundational in everything we do
• Sunny Friday Program for Calgary-based permanent employees
• Competitive compensation
• Employer paid benefits: health, dental, vision & more for permanent employees
• Team building activities and ultimately;
• We recognize people are at the core of our success

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