Job Description & How to Apply Below
READY TO CREATE INNOVATIVE SOLUTIONS AND BEST PRACTICES? Join our team. The Falcon AI Community Insights team consists of Analysts, Data Scientists, Data Engineers and Marketing Managers who are all passionate about enhancing the customer experience using the latest AI & ML technologies. Our mandate is to support the growth of Fibre networks and our customer base with meaningful and actionable insights.
We are building the next generation of Demand Forecasting, Customer Behavioral, and Intents Prediction models to deliver deeper insight into our business and support planning processes to ensure optimal outcomes for our customers.
Our team enjoys a flexible work style with the ability to work in or out of the office, in an innovative environment, that influences the direction and performance of the business.
What You’ll Do
Develop and implement ML & AI and Big Data solutions including predictive modelling, customer impact assessments, etc.
Support and evolve the AI Community Insights roadmap by leveraging industry research, best practices, and emerging tools/technology.
Execute, oversee, and evolve models and algorithms selection to deliver solutions that are relevant and facilitate decision making.
Build and maintain a robust interlock with key stakeholders to understand business needs and priorities.
Identify opportunities for process/model optimization and refine to improve effectiveness/accuracy and enhance ROI.
Collaborate with Data Scientists and Data Engineers within TELUS as well as external Data Science communities.
Qualifications
You are recognized for addressing business needs via your application of data mining and analysis, predictive modeling, statistics, and other advanced analytical techniques.
You are sought out for your skills in Machine Learning, Regression, Classification, Clustering, Segmentation, Time Series Analysis, Demand Forecasting and Optimization.
Experience developing in Python; comfortable using various data science libraries such as Scikit-learn, Pandas, Numpy as well as frameworks like Pytorch or Keras.
Comfortable with Jupyter environment and infrastructure.
Proficiency with SQL.
Experience with at least one of the major cloud computing platforms - GCP, AWS, Azure.
Well versed in software development lifecycle and ML Ops concepts.
Great-to-haves
Degree in a quantitative field such as Math, Statistics, Computer Science, Economics, or Data Science.
Data visualization experience:
Data Studio, Tableau, Power
BI, Domo.
Data environments experience: MS SQL, Oracle.
Experience with Virtual machines, Big Query and other Google Cloud Platform services.
Experience with agile methodology and team-based software development workflows (e.g. JIRA).
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