Data Scientist Google Cloud Platform

Intello Technologies Inc.; Cambridge; On-site; CAD 86,000 - 130,000; Full time

Job summary

A leading telecommunications company is seeking a Data Scientist to join its Lifecycle Marketing team. You will be responsible for building AI and machine learning models that enhance customer acquisition and marketing strategies. Ideal candidates will have 4–6 years of relevant experience, a Bachelor’s degree, advanced coding skills in Python/R and SQL, and familiarity with cloud platforms. Competitive salary, performance bonuses, and flexible benefits are offered, ensuring a dynamic work environment.

Benefits

Performance bonus of 12%

Minimum 3 weeks of vacation

Flexible benefits plan

Qualifications

• 4–6 years of Data Science experience, with 2+ years in leading projects.
• Experience in production-ready software engineering for complex models.
• Comfortable deploying models with cloud platforms.

Responsibilities

• Own complex AI/ML models or initiatives in marketing.
• Lead data discovery and analytical efforts to generate hypotheses.
• Provide data analysis and standard reporting support.

Skills

Python

R

SQL

Pandas

Scikit-Learn

TensorFlow

PyTorch

Keras

Education

Bachelor’s degree in Computer Science, Data Science or equivalent

Tools

GCP

AWS

Azure

Job description

Overview

Data Scientist – Lifecycle Marketing and Data Science within TELUS Business Solutions (TBS). Join a dynamic, fast‑paced team responsible for driving profitable growth in the Small & Medium Business (SMB) segment. You’ll work closely with Business Stakeholders and a Data Engineer to build AI/ML models that protect the customer base, acquire new customers, and enable intelligent marketing campaigns with a direct impact on sales targets and P&L.

What You’ll Do

• Own complex or new AI/ML models or initiatives in a functional domain (e.g., marketing upsell).
• Lead data discovery and analytical efforts to generate hypotheses, discover signals, patterns, and relationships that inform strategic and operational decisions.
• Provide data analysis and standard reporting support.
• Apply advanced data science techniques (e.g., NLP, deep learning, reinforcement learning) with complex data streams at different timescales.
• Understand functional use‑cases and KPIs impacted via AI/ML.
• Take end‑to‑end responsibility for complex use‑cases—conception to insight delivery—with a focus on business outcomes.
• Communicate advanced Data Science requirements and insights to Manager‑level stakeholders, create and deliver impactful presentations.

Qualifications

• Bachelor’s degree in Computer Science, Data Science or equivalent experience/certificates.
• 4–6 years of Data Science experience, with 2+ years independently leading projects/modeling.
• Advanced coding in Python/R and SQL; proficiency with Pandas, Scikit‑Learn, TensorFlow, PyTorch, Keras.
• Comfortable deploying models with cloud platforms (GCP, AWS, Azure).
• Experience in production‑ready software engineering fundamentals for complex models.

Great‑to‑have

• Design, develop, and deploy end‑to‑end AI/ML models using GCP services.
• Experience with MLOps and supporting the data infrastructure for machine learning workflows.
• Proficiency in classification, clustering, time‑series analysis, NLP, optimization, and deep learning.
• Certification on Google Cloud or another cloud platform.
• Telecom industry experience.

Compensation & Benefits

Salary Range: $86,000 – $130,000

Performance Bonus or Sales Incentive Plan: 12%

Actual total compensation will be determined based on knowledge, skills, performance and experience. TELUS offers a comprehensive rewards package, including minimum 3 weeks of vacation and a flexible benefits plan.

Job Type

This is a current vacancy.

Accessibility & EEO Statement

TLUS is proud to foster an inclusive culture that embraces diversity. We are committed to fair employment practices and all qualified applicants will receive consideration for employment. We offer accommodation for applicants with disabilities, as required, during the recruitment process.