Requisition Id : BCEJP00020548
Machine learning, Python, SQL
Benefits of working on the BI Data Science team : • Building models with petabytes of data in Canada's largest telecom with the most valuable brand • Working with cutting edge technology stack and ML infrastructure • Gaining experience to multiple industries in one company (Media, retail, home security in addition to telecom) • Teaming up with an organization that champions mental health, diversity, and social responsibility • Embedding yourself in a supportive team environment that invests in your career development • Getting time and resources to work on your ML-related side project of choice • Opportunities for training, development and passes to conferences • Casual dress code and flexible work locations • Fully subsidized unlimited phone plans and subsidized phones • Discounts with numerous internal and external partners Key responsibilities: Machine Learning Development • Build and implement machine learning-driven projects from inception to production • Frame and structure business opportunities as ML problems • Identify right and quality data sources to enable model development • Collaborate with cross functional teams of data engineers, ML engineers, project managers and business process owners in developing and deploying ML projects • Use a production-first mindset with respect to performance, time, quality and cost and through prototyping • Support business asks around model performance, explainability and strategic guidance • Maintain and expand your knowledge of ML/AI and current technology through training opportunities Business Development • Consult for the business team to identify the right opportunities to apply ML techniques • Build business case around using ML techniques to address the business opportunities • Develop minimum viable products (MVP) or proof-of-concepts to demonstrate the value of ML • Present the approach to senior business partners and get business buy-in • Build trusting relationship with existing business clients Leadership Support • Lead and assist with interviewing and onboarding of new hires • Identify and engage with external partners to create value-adding collaboration • Present your work at internal seminars and mentor junior team members • Present your work at meetups and conferences Required competencies • You have knowledge/ experience with at least one general programming language (e.g. Python, C/C++, Java). Experience in software engineering and containerization is a plus • You have knowledge/ experience of ML frameworks/ libraries (e.g. Scikit-learn, PyTorch, SparkML, Keras, Tensorflow, numpy, pandas, NLTK, OpenCV). Experience in model deployment at scale is a plus • You are highly analytical and are a natural storyteller. Experience with data visualization is a plus • You have experience with ML algorithms and techniques: supervised learning including regression, trees, SVM, and deep neural nets, unsupervised and reinforcement learning, and mathematical understanding of them. Experience in ML applications such as computer vision, natural language processing, and recommender systems is a plus • You have experience driving changes and facilitate technological transformations. Experience in consulting is a plus • Experience with data processing and storage technologies like Hadoop, Spark, Redis, HBase, Kafka, SAS and Teradata is a plus • You are self-motivated and can demonstrate enthusiasm via personal projects, Kaggle competitions, publications, contribution to open source projects, and/or presentations at meetups/conferences Description: Machine Learning Development • Build and implement machine learning-driven projects from inception to production • Frame and structure business opportunities as ML problems • Identify right and quality data sources to enable model development • Collaborate with cross functional teams of data engineers, ML engineers, project managers and business process owners in developing and deploying ML projects • Use a production-first mindset with respect to performance, time, quality and cost and through prototyping • Support business asks around model performance, explainability and strategic guidance • Maintain and expand your knowledge of ML/AI and current technology through training opportunities Business Development • Consult for the business team to identify the right opportunities to apply ML techniques • Build business case around using ML techniques to address the business opportunities • Develop minimum viable products (MVP) or proof-of-concepts to demonstrate the value of ML • Present the approach to senior business partners and get business buy-in • Build trusting relationship with existing business clients
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