Data Strategy Lead

5 months ago

Toronto, Canada Scotiabank Full time

Requisition ID: 188678

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

Purpose

Leads and oversees Customer Insights, Data & Analytics for Scotia Digital in Canada ensuring business strategies, plans, and initiatives are executed/delivered in compliance with governing regulations, internal policies, and procedures.

**Accountabilities**:

- Leads and drives a customer-focused culture throughout their team to deepen client relationships and leverage broader Bank relationships, systems and knowledge.
- Develop Strategic partnership to coordinate and implement data-driven strategies
- Partner with stakeholders to translate their business strategies and needs into data strategies, and analytics roadmaps.
- Coordinate with other analytics teams, data office, technology, security, and compliance to deliver performance measurement, and analytics solutions.
- Work collaboratively with product owners, data engineers, and, UX designers to develop a sound data strategy for each digital customer journey, taking into consideration Scotia Digital’s strategic priorities
- Proactively address reoccurring issues and impediments to avoid recurrence.
- Facilitate the creation and promote usage of data products and customer-centric solutions that drive business value
- Proactively identify and promote analytics solutions to address business opportunities or improve customer experience.
- Anticipate the analytics or data needs of stakeholders and provide tactics and solutions to address needs and opportunities.
- Present performance results and analytics solutions to executive-level business line stakeholders.
- Collaborate with business partners, ascertaining that all performance measurement and data requirements are flagged, addressed, and incorporated.
- Represent analytics in steering committees and executive engagements to present performance results and provide data-informed recommendations.
- Foster a Data-driven culture
- Liaise with product owners and technical teams to identify new sources of data to drive business innovation throughout the system.
- Enable product and design teams to be able to read, interpret and understand findings.
- Prepare and deliver workshops or education on data literacy, data and dashboard interpretation.
- Team Development
- Lead a team of data strategists and data scientists to effectively champion data-driven decision-making with business stakeholders.
- Build trust amongst the team, providing coaching and constructive feedback.
- Conduct performance reviews providing performance feedback and development opportunities to individual contributors.
- Manage team effectiveness, analyze performance metrics, and adjust focus as needed.
- Understand how the Bank’s risk appetite and risk culture should be considered in day-to-day activities and decisions.
- Creates an environment in which their team pursues effective and efficient operations of their respective areas in accordance with Scotiabank’s Values, its Code of Conduct and the Global Sales Principles, while ensuring the adequacy, adherence to and effectiveness of day-to-day business controls to meet obligations with respect to operational, compliance, AML/ATF/sanctions and conduct risk.
- Builds a high-performance environment and implements a people strategy that attracts, retains, develops and motivates their team by fostering an inclusive work environment and using a coaching mindset and behaviours; communicating vison/values/business strategy; and, managing succession and development planning for the team.

Education/Experience
- 8+ years of experience with data management, performance measurement and stakeholder management
- University degree in a relevant STEM discipline (Computer Sciences, Computer/Software Engineering, Mathematics, Statistics) or equivalent experience.
- Experience cleaning, transforming, and visualizing large data sets working with various data formats (e.g. unstructured logs, XML, JSON, flat files, audio, image)
- Proficient in one or more statistical programming languages (eg. Python, R) and have practical experience with data science tools and libraries
- Experience with Big Data ecosystem tools (e.g., Hive, Pig, Sqoop, Spark, Google Cloud Platform) and are comfortable with creating large queries
- Experience leveraging digital analytics tools such as Adobe Analytics, Google Analytics or Splunk
- Experience using and implementing visualization tools like Power BI, Tableau or QlikView
- Ability to manage process and planning, facilitate teamwork, and coordinate execution of multiple deliverables.
- Excellent analytical skills. Must be able to interpret and consolidate large amounts of information in actionable recommendations. Uses sound judgment in the creation of analysis, validation, interpretation and presentation of findings;
- Ability to manage opportunities -identifying them and helping drive their implementation
- Strong project management and

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