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Data Scientist Lead

2 months ago

Montreal, Quebec, Canada Bell Full time
Job Description

Key Responsibilities

The Data Scientist Lead will be responsible for applying best practices to extract, prepare, and manipulate multiple data sources in various technologies such as Oracle DBS, Microsoft SQL Server, Google Big Query, SAS, Teradata, Hadoop, and Python data connectors in preparation for statistical and AI/ML model deployment to identify fraud patterns. They will execute the following tasks:

  • Understand the company's fraud needs and link them to data needs by working with multiple teams and internal/external providers;
  • Participate in the entire project lifecycle by designing solutions and ensuring timely and successful project completion;
  • Prepare the implementation plan according to needs;
  • Test, develop, deploy, and modify data manipulation solutions (ETL) using Python and Alteryx;
  • Collaborate with fraud experts to apply AI, AM, and statistical models to find anomalies and fraud patterns in all available data;
  • Create reports, track key performance indicators, and support all deployed AI models (MLOps);
  • Support ad-hoc requests and investigations;
  • Find new opportunities to automate solutions;
  • Load and structure data from various environments into a centralized database;
  • Provide technical expertise and translate fraud detection team requirements to internal/external teams and providers to support new initiatives to reduce Bell's and its subsidiaries' risk exposure;
  • Ensure data validity and integrity;
  • Assume responsibility for deliverables and deadlines, communicate proactively, and report issues to management as needed;
  • Respond to ad-hoc requests in a timely manner;
  • Share expertise and mentor other team members;
  • Document experiences and produce design documentation for all solutions (e.g., data catalog/characteristics);
  • Investigate data/analytics process anomalies and propose and implement solutions;

Essential Qualifications

  • At least 5 years of experience in Python development for machine learning and deep learning;
  • At least 5 years of experience in data manipulation (ETL) development using Python and/or Alteryx and/or an equivalent ETL/ELT platform;
  • Practical experience loading and manipulating multiple large datasets in Python;
  • Practical experience deploying AI solutions in production;
  • Solid experience in SQL programming: creating complex queries, tables, views, and procedures;
  • Strong skills in programming to create reports and visualizations using the following tools: Tableau Server/Desktop, Python visualization libraries (e.g., Matplotlib, Seaborn), Excel;
  • Deep knowledge of Python frameworks and libraries for applying supervised and unsupervised AM models (e.g., Pandas, Numpy, Scikit-Learn, Scipy, Pyspark, TensorFlow, Keras, H2O, Django);
  • Expertise with cloud architectures (e.g., GCP or AWS);
  • Knowledge of API call structure;
  • Knowledge of Docker architecture;
  • Ability to work according to agile methodology (e.g., JIRA);
  • Ability to create, modify, and review application requirements documents (BRD, IRD, etc.);
  • Competence with GIT;
  • Bilingualism is an asset (English and French);
  • Bachelor's degree in Data Science or Data Engineering or equivalent;