Story Behind the Need:

• Business group: Small Business & Channel Analytics – team works in customer onboarding, using proprietary technology building to assess necessary stages that customers are onboarded safely and securely, a lot of work is focused on channel expansion, data and analytics to see how that funnel is behaving
• Project: Initiative working with an external vendor (fraud and know your customer technology) – ensuring data is properly ingested, structured, – work in coordinating with fraud, digital teams and business partners to ensure data is effectively shaped; will be building reports off the data; the contractor needs to be able to effectively assess and report and interpret reports/data – stage: through proof of concept, current coordination with vendor partners and ensuring their technologies align to ours, early stages and ramping up

Candidate Value Proposition:

• The successful candidate will have the opportunity to gain exposure to advanced technologies in big data analytics, such as Spark, GCP, Kafka; work in a top 5 Canadian Bank.

Typical Day in Role:

• Collaborate with business lines and other stakeholders and identify opportunities to drive business value by leveraging data science and data engineering solutions
• Efficiently handle large volumes of structured and unstructured data through ingestion, modeling, transformation, and storage across diverse data stores. Leverage distributed computing tools (e.g., Spark, Cloud) for analysis, data mining, and modeling
• Collaborate with operation, and other analytics teams to deploy models and algorithms in production across different channels and platforms
• Work with the team to design the project architecture and road map.
• Prepare detailed documentation to outline data sources, models, and algorithms used and developed.
• Present results to business line stakeholders and help implement real world data-driven changes.

Candidate Requirements/Must Have Skills:

• 10+ years of combined working experience with SQL, Spark and relational databases technologies/concepts for both (please list which)
• 10+ years of production experience with statistical analysis, machine learning and digital analytics (e.g., hypothesis driven analysis, acquisition, and fraud/anomaly detection)
• 3-5+ years' experience with Power BI and/or Tableau (Power BI preferable)

Nice-To-Have Skills:

• Domain knowledge/experience with on digital authentication and digital fraud analytics.
• Hands-on experience with Big Data/Cloud ecosystem (GCP)
• Experience with existing Know-Your-Customer (KYC) practices across financial institutions and the supporting technologies

Soft Skills Required:

• Excellent written, verbal, and interpersonal skills for executive level communication and collaboration
• Able to work in a fast-paced, constantly evolving environment and manage multiple priorities.
• Pragmatic and capable of solving complex issues.
• Strong experience working with a variety of cross-functional teams.

Education:

• Bachelor's Degree or equivalent in in Computer Science, Engineering, or relevant field.

Best VS. Average Candidate:

• Ideal candidate has a lot of expertise in the field and with technologies to be able to hit the ground running; need strong communication skills as will be working with a variety of teams and stakeholders – need to be able to effectively communicate and manage expectations; strong attention to detail considering technical complexity but also the existing Bank systems are highly complex, being able to understand and track that technical complexity is very valuable

Candidate Review & Selection:

• MS Team Video Interview
• 2 rounds
o 1st with HM – up to 45 minutes
o 2nd panel – up to 45 minutes – possible case study component

Job Details

11996

Contract

4.5 Months

Toronto

#J-18808-Ljbffr