Category
Technology
Job Id
429172
Req Id: 429172
Connection is everything. It drives us to innovate, explore, and stay close to what matters to us most. At Bell, we’re building a more connected future through world-class networks, AI-powered solutions, and digital experiences that elevate how people live, work, and play every day.
We believe in empowering people. That’s why we equip our teams with cutting-edge technology, AI tools, and a collaborative environment that supports creativity and growth. Want to be part of a diverse team where your work makes a real impact? If you’re inspired by innovation that advances how people connect and transforms what’s possible, you belong on #TeamBell.
Summary
We are seeking a highly motivated and experienced Senior Data Scientist I to join our team. The ideal candidate will have a strong understanding of data science principles, a proven track record of deploying robust machine learning solutions, and a passion for leveraging data to drive decision-making. The team primarily focuses on use cases for contact center optimization, building innovative data-driven solutions and applications for seamless business integration. This role offers the opportunity to drive technical direction in an innovative and collaborative team environment working on a high-impact data product.
Key Responsibilities
- Lead the end-to-end lifecycle of complex data science projects, from ideation to production monitoring.
- Design and train predictive models, including deep learning models, to optimize key business outcomes and address challenges.
- Engineer impactful features and build robust, automated data pipelines to support model training and inference.
- Rigorously analyze model performance and systematically fine-tune models to maximize business metrics.
- Build and deploy scalable, low-latency, production-grade applications to serve models in a production cloud environment.
- Use a production-first mindset to consult on project feasibility and help shape technical strategy, balancing performance, time, and cost.
- Actively partner with Product and Engineering teams to influence product design and align on solution feasibility.
- Design and validate new processes, products, and advanced ML techniques through experimentation and testing.
- Analyze large structured and unstructured datasets to identify insights and propose strategies to address complex technical challenges.
- Communicate complex findings and strategic recommendations to technical and non-technical audiences concisely and effectively.
- Proactively engage with team members to accomplish individual and groups goals, providing technical leadership and mentorship to other data scientists.
- Continuously seek new opportunities to develop and apply new skills towards the improvement of data science processes and technical methodologies.
- Establish comprehensive monitoring for model performance and data drift, using insights to drive continuous improvement.
- Document complex model architectures, deployment processes, and data pipelines to ensure maintainability.
Critical Qualifications
- Bachelor’s degree in a discipline such as Computer Science, Data Science, Engineering, Applied Math, or a related field.
- 5+ years of relevant work experience in a data science, machine learning, or analytics role with demonstrated history of project ownership and delivery
- Proven experience in designing, building, and deploying machine learning models into production environments with measurable impact
- Extensive experience working in a cloud environment (GCP is preferred, but cloud skills are transferable).
- Expert proficiency in SQL and Python, with strong ability to write clean, efficient, and reusable code for both model training and application development
- Expertise in a wide range of machine learning algorithms, statistical methods, and deep learning frameworks (e.g. scikit-learn, Keras, TensorFlow, PyTorch).
- Experience building Python-based applications to serve model predictions for online inference.
- Experience applying Natural Language Processing techniques to build solutions using unstructured data.
- Expertise with using Git in a collaborative team environment.
- Proven ability to perform statistical analysis to validate model performance and business impact.
- Strong communication and presentation skills, with the ability to convey complex technical concepts to both technical and non-technical audiences.
- Demonstrated experience leading technical projects and mentoring team members.
Preferred Qualifications
- Master’s or Ph.D. in a discipline such as Computer Science, Data Science, Engineering, Applied Math, or a related field.
- Professional certification in cloud-based data platforms and services (e.g. GCP Professional Machine Learning Engineer).
- In-depth knowledge of ML Ops principles and familiarity with associated methods/tools.
- Demonstrated experience building ML models f