Senior Data Scientist - TELUS Geospatial Insights
TELUS
Calgary, AB, CA
5d ago

Description

The IoT Industry Solutions team is "start-up" within TELUS that is focused on building end-to-end customer solutions that combine the strengths of our networks, leading SaaS and platform partnerships, our breadth of customer relationships, and the power of data insights.

We own the success of focused vertical and horizontal IoT solutions across Intelligent Mobility, Connected Workers, Smart City, Agriculture, and Health.

We're passionate about building new business areas for TELUS and will succeed by bringing clarity and focus to the challenge.

About the team

This role is part of the Data and Applied Intelligence team within IoT Industry Solutions. We are a provider of data, insights and data science services to commercial and government organizations.

Our product solves many business problems across a wide variety of industries. They are currently being used in Tourism, Commercial Real Estate, Transportation and many other industries to help decision makers plan their next course of action or analyze their historical activities.

We are a fun group of individuals, who are really passionate about our products and committed to provide quality solutions to our customers.

About the role

  • Design and build large and complex data sets, from spurious sources while thinking strategically about uses of data and how data use interacts with data design
  • Design and implement statistical data quality procedures for new data sources
  • Develop algorithms / software for accessing and handling data appropriately
  • Implement and hand off data checking and updating procedures to teams
  • Lead the new product developments for the TELUS Insights portfolio and product enhancements for existing location intelligence products
  • Scale the current custom consulting projects to a generalized product that could be reused for multiple clients across multiple verticals
  • Develop and implement ML & AI and Big Data solutions including predictive modeling,forecasting and classification
  • Visualize and report data findings creatively in a variety of visual formats that appropriately provides insights to the organization
  • Train others on what data is available and how to use various sources
  • Communicate findings to business leaders in a way that can influence how an organization approaches a business challenge
  • Support and evolve the TELUS Insights product roadmap by leveraging customer insights, industry research, best practices, and emerging tools / technology
  • 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're the missing piece of the puzzle

  • You have 5+ years of experience working with large temporal geospatial datasets
  • MSc. or PhD / Research in Computer Science, Statistics, Geospatial etc.
  • You possess deep expertise in location intelligence / Geospatial data
  • Working with structured and unstructured data sets
  • Excellent skills working with complex SQL and Spark
  • Experience developing in Python; comfortable using various data science libraries such as Scikit-learn, Pandas, Numpy as well as frameworks like TensorFlow, Pytorch, Keras
  • Experience building and architecting API endpoints
  • Experience working with telecom background is a plus
  • Experience working with cloud environments like GCP
  • 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, Classification, Clustering, Segmentation, Time Series Analysis, Demand Forecasting and Optimization
  • Evaluating and providing input on potential business intelligence solutions.
  • Comfortable with Jupyter environment and infrastructure, Spyder / PyCharm
  • Experience with at least one of the major cloud computing platforms - GCP, AWS, Azure
  • Well versed in software development lifecycle and ML Ops concepts; Developing end-end to models / projects and automation in production environment.
  • Knowledgeable about common supervised and unsupervised Machine Learning approaches (eg. feature engineering, classification, regression, clustering, NLP, time series forecasting, etc.
  • Tensorflow , Deep Learning and synthetic tabular data generation is a strong asset

    Great-to-haves

  • PhD in a quantitative field such as Math, Statistics, Computer Science, Economics, or Data Science
  • Data visualization experience : Data Studio, Tableau, PowerBI, Domo
  • Data environments experience : MS SQL, Oracle
  • Experience using Google Workspace
  • Experience with agile methodology and team-based software development workflows ( JIRA)
  • MBIOT22 #LI-REMOTE

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