Senior Data Scientist

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Requisition ID: 275751

Join a purpose driven winning team, committed to results, in an inclusive and high-performing culture.

The Role:

The Advanced Analytics & Modeling team is responsible for developing and implementing best-in-class analytics solutions to provide actionable customer-focused insights on business initiatives across the Bank, and for commercializing analytical frameworks and methodologies for use across the organization that highlight opportunities to acquire, grow and retain customers.

Within this department, the Senior Data Scientist is responsible for solving complex business problems, using quantitative approaches with a unique blend of analytical, mathematical and technical skills. The incumbent uses their technical skills to develop advanced analytical assets that will help the Bank achieve its business objectives.

The incumbent will work closely with analytics teams, business lines, data stewarts and other internal stakeholders to drive business value, and recommend solutions to drive customer acquisition, retention, balance growth, cross-sell/up-sell, product activation and usage.The incumbent will require a combination of business focus, strong analytical and problem solving skills and programming knowledge to quickly draw insights from large, disparate data sources to support Bank strategies.

Excellent written and communiation skills are requiried and the Senior Data Scientist will work closely with the Director, Advanced Analytics & Modeling to conduct analytics and report back findings in a clear and structured manner.

Finally, the incumbent is responsible for developing and mentoring a team of senior level analytic staff, and instilling a customer-centric view of analysis within the organization.

Is this role right for you? In this role you will:

• Collaborate with stakeholders in identifying opportunities for leveraging data and use of ML algorithms to develop innovative solutions and solve complex business problems
• Design, develop, and implement end-to-end machine learning production pipelines (data exploration, cleaning, feature engineering, model building, and performance evaluation) and ensure that pipelines are scalable, repeatable, and secure, and can serve multiple users within the company.
• Present and depict the rationale of findings in easy to understand terms for the business or senior management.
• Support analytical use-case delivery, as well as customer/financial benefits tracking and communication
• Apply statistical, analytical and programming skills to analyze and interpret large data sets and communicate results and methodologies to business clients and senior members of the analytics team.
• Prepare detailed documentation to outline data sources, models and algorithms used
• Leverage distributed computing tools (e.g. Spark, Hadoop) for analysis, data mining and modeling to provide actionable insights to decision makers within the Bank.
• Collaborate with Data engineering team to implement and manage MLOps best practices, establishing continuous integration, continuous delivery, and model monitoring pipelines to ensure reliability and performance in production.
• Be an integral part of the Advanced Analytics community for incubating ideas and use case acceleration in all business lines through advisory, training and scalable solutions
• Stay current on trends in the data science and fin-tech product space, translate those trends into actionable strategic and tactical objectives for the company.
• Contribute to a culture of innovation inside and outside of the company as a visionary capable of inspiring through presentation, demonstration and leading by example.
• Provide strong leadership and mentoring to junior data scientists and motivate both individual and team performance and foster a commitment to the Bank’s objectives.
• Ensure that the Bank has the capabilities and skill sets to compete develop a competitive advantage in analytics over other financial institutions

Do you have the skills that will enable you to succeed in this role? We'd love to work with you if you have

• University degree in relevant STEM discipline (Computer Sciences, Electrical/Computer/Software Engineering, Mathematics). Master’s Degree or Ph. D preferred.
• Excellent understanding of Machine Learning algorithms for forecasting, predictions, segmentation.
• Solid analytical skills. Must be comfortable working with large amounts of information in cloud environment and translating data into clear and concise findings.
• Strong communication and interpersonal skills. Boardroom level oral/written communication & presentation skills in a client-facing setting.
• Strong Python and SQL (BigQuery/MySQL‑compatible) expertise for data wrangling, exploratory analysis, and feature engineering using Pandas, Jupyter, and BigQuery.
• Hands‑on experience building and evaluating machine learning models using Scikit‑Learn, XGBoost, Boruta, and BigQuery ML, with exposure to PySpark ML, TensorFlow, and PyTorch.
• Proven ability to design end‑to‑end data and ML pipelines on GCP, leveraging Airflow (Composer) for orchestration and dbt for scalable data transformations (models, macros, seeds, Jinja).
• Experience with DevOps tools (Git, Azure DevOps, CI/CD, Databricks Workflows, Airflow) and Docker concepts would be an asset
• Experience working with Big Data and distributed processing using PySpark, with solid understanding of Spark fundamentals and large‑scale data processing concepts.
• Strong background in data visualization and storytelling, using Plotly, Matplotlib, and Seaborn to communicate insights and model results to stakeholders.
• Working knowledge of strategy optimization leveraging operations research principles would be an asset. Knowledge of the Bank's products and services an asset.

What's in it for you?

• Diversity, Equity, Inclusion & Allyship - We strive to create an inclusive culture where every employee is empowered to reach their fullest potential, respected for who they are, and are embraced through bias‑free practices and inclusive values across Scotiabank.
• We embrace diversity and provide opportunities for all employees to learn, grow & participate through our various Employee Resource Groups (ERGs) that span across diverse gender identities, ethnicity, race, age, ability & veterans.
• Accessibility and Workplace Accommodations - We value the unique skills and experiences each individual brings to the Bank and are committed to creating and maintaining an inclusive and accessible environment for everyone. Scotiabank continues to locate, remove and prevent barriers so that we can build a diverse and inclusive environment while meeting accessibility requirements.
• Upskilling through online courses, cross‑functional development opportunities, and tuition assistance.
• Competitive Rewards program including bonus, flexible vacation, personal, sick days and benefits will start on day one.
• Community Engagement - no matter where you choose to work from; we offer opportunities for community engagement & belonging with our various programs such as hackathons, contests, Humans of Digital and much more!

Location(s): Canada : Ontario : Toronto

Scotiabank is a leading bank in the Americas. Guided by our purpose: "for every future", we help our customers, their families and their communities achieve success through a broad range of advice, products and services, including personal and commercial banking, wealth management and private banking, corporate and investment banking, and capital markets.

At Scotiabank, we value the unique skills and experiences each individual brings to the Bank, and are committed to creating and maintaining an inclusive and accessible environment for everyone. If you require accommodation (including, but not limited to, an accessible interview site, alternate format documents, ASL Interpreter, or Assistive Technology) during the recruitment and selection process, please let our Recruitment team know.

We thank all applicants for their interest in a career at Scotiabank; however, only those candidates who are selected for an interview will be contacted.