As a Data Scientist on our team, you'll design, develop, and deliver machine learning solutions, decipher loosely defined problems using complex datasets, and determine appropriate analytical and modeling techniques. You'll analyze structured and unstructured data, establish automated processes for large-scale modeling, perform exploratory analysis, and collaborate with peers on data acquisition and exploration, demonstrating a strong sense of ownership and urgency.
Responsibilities
- Work on all aspects of the design, development and delivery of machine learning
enabled solutions for our clients;
- Come up with solutions to loosely defined business problems by leveraging pattern
detection over complex datasets across multiple platforms;
- Determine analytical approaches and modeling techniques to evaluate scenarios and
potential future outcomes;
- Analyze and interprets data from structured and unstructured data sources in both batch and streaming modes;
- Establish efficient, automated processes for large-scale modeling.
- Perform ad-hoc exploratory and explanatory analysis.
- Become part of a highly skilled and geographically distributed team.
- Collaborate with peers on problem definitions, data acquisition, data exploration, visualization as well as building the tools that support this process.
- Strong sense of ownership, urgency and drive.
Qualifications
- A Bachelor and/or Master degree in Statistics, Mathematics, Physics, Computer Science or other related subject
- Strong command of statistical programming languages (especially R and Python)
- Model development in Python (machine learning, recommendation engines)
- Big Data Hadoop work experience (either integration the models with the tools in Hadoop or other)
- Software development experience from scoping, requirements design, development, integration, testing, go live to PROD (vs internal research work)
- Experience working with Bank raw data (credit card, customer, product, real-time and batch)
- Other programming experience (Spark, SAS, Scala, Java, etc.) is a huge plus
- Experience in working with large datasets and relational databases is highly desirable (SQL)
- Ability to work on distributed cloud platforms
- Exceptional written and verbal communication as well as presentation skill
- Curiosity and an investigative profile: you’re a data-driven problem solver!
What’s in it for you:
- Private medical and life insurance from day one
- Employee Stock purchase plan ESPP
- Budget for professional growth (certifications)
- Schedule flexibility.
- Extra bonus based on performance.
Additional Job Description
As a Data Scientist on our team, you'll design, develop, and deliver machine learning solutions, decipher loosely defined problems using complex datasets, and determine appropriate analytical and modeling techniques. You'll analyze structured and unstructured data, establish automated processes for large-scale modeling, perform exploratory analysis, and collaborate with peers on data acquisition and exploration, demonstrating a strong sense of ownership and urgency.
EEO Statement
At TELUS International, we enable customer experience innovation through spirited teamwork, agile thinking, and a caring culture that puts customers first. TELUS International is the global arm of TELUS Corporation, one of the largest telecommunications service providers in Canada. We deliver contact center and business process outsourcing (BPO) solutions to some of the world's largest corporations in the consumer electronics, finance, telecommunications and utilities sectors. With global call center delivery capabilities, our multi-shore, multi-language programs offer safe, secure infrastructure, value-based pricing, skills-based resources and exceptional customer service - all backed by TELUS, our multi-billion dollar telecommunications parent.
Equal Opportunity Employer
At TELUS International, we are proud to be an equal opportunity employer and are committed to creating a diverse and inclusive workplace. All aspects of employment, including the decision to hire and promote, are based on applicants’ qualifications, merits, competence and performance without regard to any characteristic related to diversity.
