Senior Security Consultant - Data Analytics

Join our team and what we'll accomplish together

The Fraud Analytics team is uniquely positioned to prevent, monitor, detect, respond and remedy fraud. We oversee fraud management for multiple: lines of business, brands, customer segments and all service distribution channels. 

While we are an operational team we are looking to expand our strategic focus through data analytics and rich insights that lead to intelligent fraud pattern detection and process/system improvements to prevent fraud.

We live in a fast-paced world where protecting our customers and TELUS is paramount; we are tackling intricate fraud challenges head-on with top talent and working to employ cutting edge technology. 

• Security is the place to be; with increase digitization of our life customers, vendors and organizations need for security has dramatically increased
• We are a dynamic team that works together to find new innovative ways to protect TELUS and our customers
• An environment where you’re encouraged to share and act on your ideas, while learning new things and building your career
• An opportunity for the lifetime learner to be part of a unique business function and learn the intricate ways of fraud and its management
• Able to work flexible hours and connect remotely with team members across Canada
• A culture committed to giving back to our communities; every year we donate time and resources in our communities
• Access to well-being resources as well as ongoing support and focus on overall team member physical and mental well-being

What you will do

• You have in depth experience with data analytics, TELUS metadata and its data sources across multiple lines of business. You have expertise in data modeling tools and can evangelize, lead and educate on the use of such tools. 
• You will use advanced data analytics and data modeling to create structures where structure is lacking, and provide quantitative models and statistical analysis to help predict where and how fraud will happen.
• You will help us research and develop key metrics and innovative modeling capabilities, solutions, and tools for continuously improving fraud prevention and detection processes.
• You will use rich insights to “tell the story” that generate action based on “real life” activity 
• You will focus primarily on data and reporting requirements and provide support for new and existing data analytics solutions 
• By being focused on the data, reporting, and analytical modeling, you provide subject matter expertise and thought leadership to our team’s data analytics frameworks.  
• You will drive a cultural change across the organization and evolve how we make data-driven decisions

What you bring

• 7-10 years of experience working with data analytics tools and methodologies.
• An in-depth knowledge of database querying, data mining, and statistical and predictive models and algorithms.
• Fluent in programming languages – SQL, SASS, VBA
• Expertise with data analytics visualization tools such as: Google Data Studio, Tableau, DOMO
• Highly motivated with an ease/desire to question existing processes and assumptions.
• Being a collaborative team player with the ability to work on high-impact, high-visibility initiatives.
• Proficiency in translating data insights into functional/operational requirements, and translating business issues into analytical modeling and data insights.
• A strategic mindset which keeps the “big picture” in mind even while working in the details.
• Able to manage a diverse and dynamic workload, with the ability to understand new concepts and ideas quickly.
• You are a strong decision maker with the ability to pivot, when needed.
• You are proactive, open minded, and action-oriented, and not afraid to “fail forward” and learn from mistakes.
• You continuously look for inefficiencies and are always thinking about how we can make things better.

Great to haves

• Degree in Computer Science or Engineering
• Experience in/ ability to learn other programing languages: R, Python, Java 
• Experience with/ability to learn non relational datastores (e.g jasonB) 
• Understanding of AI and ML concepts of automation, decision, recommendation, and evaluation of such models