Data Analyst

Location Address: Hybrid - 44 King Street W 7th Floor, Toronto –as of now, mandate is to come in 4x/week starting in September, this is subject to change for the team - want candidates in the GTA who are OK with this
Contract Duration: ASAP to Nov 30 –
Good possibility of extension
Schedule Hours: 9am-5pm Monday-Friday;standard 37.5 hrs/week


Story Behind the Need
Business group: Technology Program Management & Transformation –team that manages cloud data integration and governance for IB, providing efficient and standardized solutions that enable different business areas to access and use data securely and effectively.

Project: International Banking –Data Migration and Transformation to Cloud
Mission: To develop and maintain a cloud platform that integrates data from various sources, standardizes processes, and facilitates data publication for consumers and producers, ensuring quality, security, and accessibility.
Scope: The primary objective of this project is to design and implement a unified cloud data platform for IB across different countries.
Impact: Efficient ingestion of data from multiple on-premises sources to the cloud.
Data transformation and standardization into organized layers (landing and standardization zones).
Rapid data delivery for bank teams requiring reports, indicators, or advanced analysis.
Incorporation of reusable data products for transversal consumption across the organization.
The project prioritizes agility in delivery, enabling tactical solutions (quick, connected to local sources) when necessary, while promoting progressive advancement toward fully cloud-based strategic solutions.

Purpose:
We are seeking a skilled Data Analyst with a strong focus on data discovery and collaboration with Subject Matter Experts (SMEs) to join our dynamic team. The ideal candidate will excel at identifying, exploring, and analyzing complex datasets to uncover actionable insights while working closely with SMEs to ensure data solutions align with business needs. This role requires strong analytical skills, effective communication, and the ability to translate technical findings into business-relevant recommendations.

Candidate Value Proposition:
Data Discovery & Exploration:
•Identify, collect, and assess relevant datasets from internal and external sources to support business objectives.
•Perform exploratory data analysis (EDA) to uncover patterns, trends, and anomalies.
•Validate data quality, integrity, and consistency, addressing issues through cleansing and preprocessing.
•SME Collaboration:
•Partner with SMEs across departments (e.G., finance, marketing, operations) to understand business requirements and domain-specific challenges.
•Facilitate workshops, interviews, and discussions to gather insights and refine data-driven solutions.
•Translate SME feedback into actionable data requirements and ensure alignment with analytical outputs.
•Data Analysis & Reporting:
•Develop and maintain dashboards, visualizations, and reports using tools like Tableau, Power BI, or similar.
•Conduct statistical analysis and modeling to derive insights that inform strategic decisions.
•Present findings to stakeholders in clear, non-technical language, tailoring insights to audience needs.
•Process Improvement:
•Identify opportunities to streamline data discovery processes and enhance data accessibility for SMEs.
•Document data sources, methodologies, and findings to support reproducibility and knowledge sharing.
•Contribute to the development of data governance and best practices for data handling.

Candidate Requirements/Must Have Skills:

• 5 - 7(max) years of experience in data analysis, data mapping, and data modelling.
• Proven track record of working with SMEs to deliver data-driven solutions.
• Proficiency in SQL for querying and manipulating large datasets.
• Experience with Python, R, or similar for data analysis and visualization, such as BI tools (e.G., Tableau, Power BI) for reporting and dashboard creation.
• Experience with cloud-based data platforms (e.G., AWS, Azure, Google Cloud).
• Spanish-speaking candidates mandatory

Nice-To-Have Skills:

• Knowledge of data warehousing concepts, pipelines and ETL processes.
• Knowledge of advanced statistical techniques or machine learning fundamentals.
• Familiarity with Agile or Scrum methodologies.

Education:

• Bachelor’s degree in Business Administration, Data Analytics, Computer Science, or related field.
• A Master’s degree is considered an asset.

Best VS. Average Candidate:
The best candidate will have hands-on experience with data visualization tools, a solid understanding of data modeling, and a proven ability to work effectively in collaborative team environments. They should also have experience working with big data technologies and managing large-scale databases.
This combination of technical expertise and teamwork is essential for transforming complex data into actionable insights and supporting data-driven decision-making across the organization.

Candidate Review & Selection
2 rounds –MS Teams Video Interviews –going through experience, testing language skills, there may be a technical assessment
1st –with Hiring manager and possibly Project manager, and Data Lead –30 minutes
2nd –with HM (Data Science Director) –30 minutes