Alternance - Data Scientist en contrat d'apprentissage F/H
4 weeks ago
At Interac, we design and deliver products and solutions that give Canadians control over their money so they can get more out of life. Whether we’re leading real-time money movement, driving innovative commerce solutions like open payments for transit systems, or making advancements in new areas like verification and open banking, we are playing a key role in shaping the future of the digital economy in Canada.
Want to make a lasting impact amongst a community of creative thinkers, problem solvers, technical gurus, and high-performance application developers? p>
The Data Scientist will be responsible for providing actionable insights for the fraud management practice. The main objective for this role will be to work with various fraud teams and other internal business partners, developing data science products (models, features, insights) to aid in fraud mitigation.
In this role, the Data Scientist will focus on fraud research and model development for new Interac products coming to market. Working on a team, developing novel features, and implementing fraud detection solutions, as well as participating in product strategy discussions will be expected. Additionally, this role will involve cross collaboration between subject matter experts in the fraud space, the business, and the technical product design teams.
The Data Scientist will work with a variety of people to provide deliverables that include research insights, product design input, and data science assets (models, tables, visualizations, etc.) These assets will ensure that Interac products are trusted, giving our business partners and end-user customers confidence that they can use any new Interac products safely. It is crucial that these deliverables provide solutions that are reproducible, well-documented, peer-reviewed, and version controlled.
Using a full-cycle data science approach, the Data Scientist will need to understand problems and surrounding context between fraud and the business need, formulate a hypothesis on how to solve these problems, and execute, providing status updates as needed. p>
You'll be responsible for:
- Collaborating with fraud product owners and software developers to enable deployment of fraud solutions that will scale across the company’s ecosystem.
- Working with large complex data sets to solve difficult, non-routine analysis problems applying advanced analytical methods as needed.
- Conducting end-to-end analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.
- Collaborating with business customers and fraud product owners to understand needs, recommend strategy enhancements, and deploy predictive analytics across multiple platforms.
- Researching, developing, deploying and analyzing testing strategies to continuously improve current fraud-related deliverables.
- Preparing detailed documentation to transfer knowledge and satisfy governance and regulatory concerns.
- Communicating technical fraud solutions to non-technical audiences.
- 3 years or more of experience in data analytics.
- 2 years or more of experience using machine learning.
- A strong sense of planning, priority setting, problem resolution, and decision making.
- Expert knowledge of data mining, databases, SQL, and machine learning.
- Experience with the following technologies/databases: Oracle, HDFS, Redshift, Spark (PySpark), Python.
- Strong knowledge of the Canadian payment industry, payments transaction data, and process flows.
- Knowledge of IT processes and infrastructure required to support analytics.
- Significant experience working with implementing concepts, such as predictive modeling, profiling, feature development, behavioral analysis, clustering, and data mining.
- Familiarity with Cloudera, Jupyter, Github, AWS is an asset.
- If applicable, Credit Inquiry and Social Media Check.
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