Your role:

As an active member of TELUS International, you will be at the heart of the major TELUS transformation program supporting it as a Data Scientist.

Required Skills:

• Bachelor’s degree in Applied Math, Statistics, Data Science/Analytics, Engineering, or a related technical degree.

• Proven ability to learn things quickly and stay up to date on breakthroughs in Data Science techniques.

• Experience with at least one of the following programming languages: Python, R, or Golang

• Comfortability with manipulating data using Python or SQL.

• Experience with common statistics methodologies such as clustering, regression, forecasting, classification, regularization, resampling, etc.

• Proficiency in using query languages such as SQL, Hive, Pig

• Experience with NoSQL databases, such as MongoDB, Cassandra, HBase

• Experience with Apache Solr, ElasticSearch, or other search tools.

Qualifications:

• Great communication skills - someone who is passionate about evangelizing the value of advanced data science capabilities.

• Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests

• Experience with AWS/GCP

• Master’s Degree and/or Ph.D. in Applied Math, Statistics, Engineering or a related field

• Good scripting and programming skills 

Competences:

• Building models and tools to get value out of the mass amounts of data we have in our environment

• Enabling the best, most personalized, and resilient customer experience possible

• In order to be successful in this role, you will need to be…

• Highly motivated, driven & hardworking

• Not afraid to fail and comfortable working independently and with a team

• Comfortable working with massive datasets in real-time and batch processing with superior analytics skills

• Comfortable talking to and working with Senior Executives

• Apply data mining techniques, statistical analysis, and build high-quality prediction systems integrated with our product. Doing ad-hoc analysis and presenting results in a clear manner.

• Processing, cleansing, and verifying the integrity of data used for analysis

• Enhancing data collection procedures to include information that is relevant for building analytic systems

• A team player. We have a great group of diverse folks working together in harmony.  Big egos and “superheroes” need not apply.