Data Scientist

Key Skills

C++, Continuous Integration & Continuous Delivery - CI/CD, Dash framework, Data science techniques, Database testing, Databricks, French language, Java Programming, Keras software library, Kubernetes-K8s, MLOps tools, Natural Language Processing (NLP), Natural Language Understanding-NLU, NumPy, Pandas, Python Programming, PyTorch, R Programming, REST API, SAS, Scikit-learn, SPSS Statistics, SQL, TensorFlow

Job Description

As one of the world’s leading global IT and business consulting services firms, CGI works across the globe with a wide variety of clients in a diverse set of industries. We also develop and deliver a vast array of business and technology solutions.

Our employees work in a highly multifaceted, fast paced environment where they work closely with our internal and external clients. We are on the groundbreaking of technology, exploring exciting areas of our clients and our business while keeping up the standard of being leaders in the industry. You will develop your career in a meaningful way and be part of our hardworking and dedicated team. Reach your full potential thanks to learning materials & training, mentoring & coaching, as well as ongoing recognition and feedback programs and career opportunities!

The Data Scientist conducts detailed analyses on data sets and proposes solutions to business challenges in advanced analytics and artificial intelligence by leveraging statistical methods, machine learning methods and optimization methods.

This person reports to the Artificial Intelligence Practice Lead and is part of a team that oversees the foundation of CGI's Artificial Intelligence Practice in Montreal. This Practice is focused on developing solutions and longer term products in artificial intelligence for our multi-sector and multi-industry clients.

This transformation plays a key role in distinguishing the company from its competitors and ensuring its sustainable growth.

Your future duties and responsibilities:

The selected candidate will divide his or her time between the implementation of Data Science best practices within the Practice, the experimentation, optimization and operationalization of innovative PoCs, and ad hoc expertise mandates for clients in various industry sectors. Above all, we are looking for someone with a good attitude, high energy, and a focus on execution and accountability.

Someone who will work with our customers and our teams, software engineering, data engineering and solution architects to provide them with the best approach and the best tools and models.

You will be expected to lead other data scientists and other technical profiles.

Key Responsibilities

• Apply statistical and machine learning insights to specific business problems and data
• Apply strong quantitative skills, experience with the use of scientific analysis methods, qualitative methods, quantitative analysis techniques.
• Exploit (data mining) and model various data (operational data, sensory data, HR data etc...)
• Develop predictive, classification and recommendation models, optimize and test them.
• Process structured and unstructured data (social media, videos, etc.)
• Develop and operationalize marketable tools with a good level of presentation (user interface, reporting)
• Propose and develop effective business intelligence solutions aligned with client needs (internal CGI & clients)
• Implement initiatives to support data engineering teams, solution architects and software engineers
• Interpret, translate and communicate analytical results to internal and external stakeholders
• Solve complex analytical problems using quantitative approaches
• Collaborate with teams to implement data best practices
• Work in an agile environment that includes regular meetings and sprints

Expected Capabilities:

• Knowledge of AI, Machine Learning, and Deep Learning with a strong ability to challenge models and algorithms and an openness to using known, peer-validated gas pedals or creating new ones.
• Know the fundamentals and requirements for implementing the MLOps framework
• A strategic thinker: A cross-functional strategic thinker who can rally managers around analytical and statistical approaches
• Code scaling of an existing model
• Deploying the scaled model in production
• Identify and monitor model drift and how to re-train a distorted model in production
• Create CI/CD pipelines to automatically deploy trained/re-trained models to production in the context of the MLOps methodology
• Ability to work independently on tasks and deliver high quality work
• Ability to learn quickly and adapt to a fast-paced environment
• Ability to work directly with the client to understand and meet their needs
• Excellent oral and written communication skills: must communicate effectively with technical and non-technical teams
• Ability to work in a team environment and be open to input and feedback
• Inspire others through effective communication and adapt to the audience in speaking and writing
• Use analytical thinking
• Innovate through problem solving
• Know the business and keep abreast of industry trends to develop expertise and do the job better
• Demonstrate good organizational skills
• Collaborate with key internal stakeholders to increase productivity
• Work independently with little supervision

Required qualifications to be successful in this role:

• Proficiency in programming languages: Python, R, SAS, SPSS, S+, Maple, C++, SQL, Excel, LaTeX.
• Proficiency in deep learning frameworks such as: Keras, Tensorflow, PyTorch, Fastai, SciKitLearn, Pandas, Numpy,
• Mastery of Machine Learning architectures/algorithms: Xception, ResNet, EfficientNet, Faster RCNN, Mask RCNN
• Mastery of the MLOps manufacturing cycle
• Knowledge of open libraries and development frameworks in the Natural Language framework (NLP-NLU)
• Knowledge of Kubernetes and containerization
• Knowledge of ML tools in cloud environment (azure or other)
• Knowledge of advanced statistical analysis: segmentation, maxdiff, conjoint analysis, factorial analysis
• Fluency in French and good level of English, both oral and written.
• Practical experience in SQL and database coding
• Knowledge of Databricks
• Knowledge of Java.