Lieu:
1 Presidents Choice Circle, Brampton, Ontario, L6Y 5S5
C’est toute une décision que de se joindre à une entreprise. Nous offrons des perspectives d’emploi à des personnes qui, comme vous, sont travaillantes, dynamiques et fiables.
Pourquoi ce role est-il important?
A t Loblaws, we know that our customers expect the very best from us. Whether that means building the best, most innovative customer experience through targeted recommendations, or designing an app or design decision engines for logistics/resource optimizations in real time that will impact the lives of people across the country, we’re up for the challenge. The Data Insights & Analytics (DIA) division is transforming the methodologies used to personalize our customer's experience. To enable this, we build scalable, reusable data-driven ML approaches to build the state of the art. Join us in this dream to build & scale.
Our data story
As Canada’s largest retailer, with well-established and widely-used loyalty programs, we have an enviable wealth of data at our disposal – and it’s now time to deploy it in the service of an evolving and superior customer experience. The Solutions Engineering team here seeks passionate individuals to build & deploy scalable ML products, and who share the same purpose to fearlessly embark on this adventure with us. We are more than just analytics: we ship actual products, in the form of models that directly impact user experience.
We’re looking to increase the engineering horsepower of our analytics teams so that we can work seamlessly integrate with analytics teams to build & deploy models at scale. We’re looking for a solid software engineer with a data science background who is comfortable in both worlds, can contribute to ambitious ML-based projects, but also help us to write reliable microservices and stream-processing systems to deliver data and insights downstream at the pace required by the business. Experience working with NLP and/or ML techniques is preferred, though is secondary to your software engineering skillset for this role.
Responsibilities:
Work cross-functionally with engineering, product, and data science/analytics teams to productionize the data science models at scale through a Service Oriented Architecture (SOA)
Develop robust, high performance batch/streaming solutions for transforming the various data sources produced by other parts of the business into training data, inputs to models, and actionable insights
Build & maintain feature pipelines to curate operational data as analytical features
Develop predictive models to help inform business decisions based upon shifts in consumer behavior.
Consult on analytical architectures and provide engineering support for build, dev and validation phases of data products within analytics teams.
Minimum qualifications:
Technical Skills:
BA/BS in math, engineering, computer science, or related technical field, or equivalent practical experience
Proficient in at least 1 compiled language, and at least 1 other programming language
Familiar with the concepts and idioms of functional programming
Familiar with concepts and programming analogues in distributed compute vs. single threaded (Pandas/numpy/scikit-learn) and refactoring experience from the latter to former using (Pyspark/Dask/etc)
Demonstrable superiority working with spark ecosystem (RDD,Dataframe, Spark-SQL, koalas, Spark mlib) and ability to tune/optimize spark code.
Comfortable with at least some of the latest “big-data” tools, such as spark, kafka, hive, beam, etc.
Experience with at least one modern REST framework (flask/Sinatra/express/etc)
Experience building with Microservices architecture
DAG orchestrations using workflow management systems – Airflow, Luigi
DevOps experience with Dockers, Git (Bitbucket/Gitflow), Jenkins
Experience with cloud environments such as Databricks/GCP/Azure
Soft Skills:
Critical thinking mind who likes to solve complex problems, loves programming, and cherishes to work in a fast-paced environment.
Ability to communicate effectively to internal and external stakeholders in writing and in person.
Extremely well organized, proactive.
Ability to multi-task and prioritize workloads.
Preferred qualifications:
MS or PhD in math, engineering, computer science, or related technical field, or equivalent practical experience
Familiar with JVM languages and associated ecosystem
Experience with one or more of the following: Natural Language Processing, text understanding, classification, pattern recognition, recommendation systems, targeting systems, ranking systems or similar
Experience with developing python and pyspark applications
Familiarity with MLOps tools (Mlflow/DVC/AzureML/etc)
Deployed machine learning models in GCP environment or basic familiarity to Kubernetes/Kubeflow.
Comment R é ussir:
Chez Loblaw, nous recherchons toujours des personnes formidables pour continuellement renforcer notre culture. Nous croyons que les gens formidables façonnent nos valeurs, sont authentiques, bâtissent la confiance et créent des liens.
Si cela vous ressemble et que vous êtes ouvert d’esprit, que vous avez une bonne attitude face aux changements et que vous aimez les défis d’un environnement de travail aux détails dynamiques, postulez aujourd’hui.
En outre, nous croyons que la conformité aux lois consiste à faire ce qu'il faut. Le respect de la loi fait partie de notre Code de conduite; il renforce ce que nos clients et nos parties prenantes attendent de nous.
Type d'emploi:
Temps plein
Role:
Poste régulier
Type of Contract:
Loblaw considère que la diversité culturelle du Canada est une source de fierté nationale et un symbole de force. Nous nous sommes donné comme priorité de refléter la diversité croissante du Canada dans les produits que nous vendons, les gens que nous embauchons et notre culture d’entreprise. Des accommodements sont disponibles sur demande pour les postulants et collègues atteints d’un handicap.
Remarque : Si vous avez accès à Libre-service de l’employé (ESS) dans Workday, veuillez postuler à cet emploi en utilisant l’application Workday.