Data Scientist

Summary

We are seeking a highly skilled Data Scientist to join a dynamic and collaborative Data Engineering and Artificial Intelligence team. The ideal candidate will be responsible for a key ML product and making a large and quantifiable impact on improving our customers’ experience and driving value for the business. You will work with highly collaborative teammates, grow your ML and analytic capabilities, and build relationships with stakeholders across multiple levels of management. 

Bell’s Data Engineering and Artificial Intelligence unit is composed of specialized teams that are responsible for data management, machine learning models, and machine learning architecture that support Bell’s diverse and complex business needs.

Key Responsibilities

• Design, build, and productionize ML models for new use cases, and retrain models used in active use cases
• Explore new data sources to uncover new business opportunities and identify opportunities to improve our existing modelling approach
• Work with stakeholders across Bell to ensure our ML product meets their evolving business needs
• Work with and present to all management levels
• Maintain and expand your knowledge of ML/AI and current technology through training opportunities, conferences, etc.
• Actively seek and implement new ideas and innovative solutions, proactively exploring new areas and opportunities for growth.
• Demonstrate a deep understanding of customer needs, anticipating and exceeding expectations to drive customer satisfaction.
• Masterfully applies systematic problem-solving methodologies to complex challenges, consistently delivering effective solutions.
• Proactively investigates mistakes, fosters a culture of learning from experience, and actively seeks opportunities to expand skills and responsibilities.

Critical Qualifications

• Bachelor’s degree in Statistics, Machine Learning, Computer Science, or a related discipline. Master’s degree is an asset
• 3+ years of work experience as a data scientist, machine learning engineer, or in a related capacity
• Algorithms
  • Intermediate knowledge of machine learning models, including deep learning, reinforcement learning, natural language processing (NLP), and other approaches; practical understanding of model selection, training, validation, and evaluation.
  • Hands on experience with major AI/ML frameworks and tools, e.g., Keras, PyTorch, TensorFlow, Spark ML, and scikit learn.
  • Familiarity with generative AI (GAI) techniques and architecture and their practical applications.
  • Ongoing awareness of emerging techniques, research trends, and best practices in the AI/ML space.
• Coding
  
  • Intermediate Python development skills
  • Good code design (OOP, Algorithms, and Data Structures) and knowledge of best practices
• Data and analysis
  
  • Intermediate SQL ability
  • Understanding of A/B testing, bias, and study design
  • Ability to analyze data to determine trends, quantify impact, and derive insights
• Collaborates and communicates effectively