Data Scientist

3 weeks ago


Brampton, Canada Rogers Communications Full time

We are looking for **Data Scientist** to join our team to develop, and maintain AI / ML models in support of AI Nerve Centre at our **Vancouver or Greater Toronto Area location**. This is a key role in building solutions by turning data into actionable ML insights through conceptualizing, designing, developing analytical solutions as required. ML Activation will be across Roger’s business units, channels and care and marketing platforms. We have a long history of investing in the next generation, and we’re committed to making Rogers the top destination for young people to start and grow their careers in Canada. In 2020, we were named one of Canada’s Top Employers for Young People for the 10th time, and in 2021 we were named one of LinkedIn’s Top 25 Companies to work for in Canada. At Rogers, your journey is filled with limitless possibilities - let’s make your possible.

**This role is Full time Temporary for 12 months.**

**Detailed responsibilities include**:

- Provide Data and Predictive AI + ML Strategy input throughout the design, development and deployment stages of the AI Nerve Centre Platform
- Lead the utilization of advanced Machine Learning tools and analytics frameworks including: AML - Azure Machine Learning, ADB - Azure Databricks, and ADO - Azure Dev Ops
- Build, architect, and maintain AI platform to empower and accelerate AI research and delivery of ML model REST APIs while maintaining cost efficiency
- Build high quality data cleansing and aggregation processes with associated testing and monitoring to prevent corrupt data from flowing in our ML models
- Build and maintain an expanding set of predictive models in support of the Campaign, Operations and Personalization strategies
- Collaborate with Strategic Insights, Marketing, Sales and BU teams in the development and deployment of the predictive models across Channels
- Monitor the model performance and make ongoing corrections by executing extensive model testing strategies
- Create dashboards with insights on the underlying data using visualization tools (such as Tableau and Power BI)
- Collaborate with IT Infrastructure teams in monitoring therefore ensuring ongoing stability
- Prepare model development and deployment documentation

**Qualifications**:

- Passionate about data science, technology, analytical models, machine learning, quantitative modelling, data visualization, software development and automation
- Solid understanding of the MLOps lifecycle
- Proficiency in DevOps tools such as Jenkins, GitLab CI/CD, or similar technologies
- Experience with containerization technologies like Docker and container orchestration tools like Kubernetes
- Demonstrated expertise in working with large modeling datasets
- Excellent understanding of the underlying Statistical, Machine Learning theory and Predictive Modeling Lifecycle
- Write high quality code with unit tests, data tests, and perform code reviews
- Effective and professional communication to understand stakeholder needs and to provide timely updates on project progress
- Experience working with Stakeholders/Business Units to deliver automated ML Ops solutions to meet their needs
- Ability to get along with people; Self-motivated, eagerness, and enthusiasm
- Proven ability to work in a team focused environment
- A mindset of creativity, innovation, and energetic drive to succeed
- You have strong software engineering skills and strong programming skills in Python/Pandas/ML Libs
- Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and their DevOps services
- Degree in Machine Learning, Statistics, AI, Computer Science or a related field, Masters degree preferred
- Must have excellent writing, presentation, and communication skills.

Schedule: Full time
Shift: Day
Length of Contract: Not Applicable (Regular Position)
Work Location: 8200 Dixie Road (101), Brampton, ON
Travel Requirements: Up to 10%
Posting Category/Function: Technology & Information Technology
Requisition ID: 300307

Posting Notes: Technology


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