Senior Data & Trust Partner at TELUS enhancing data governance and AI capabilities. Collaborating with leadership to implement trust strategies and improve organizational design.
LP
Data Scientist – Python/SAS/SQL & AI/ML Solutions
Posted via LinkedIn Recruiter (not a company profile)
Posted 4 months ago
About the role
- Data Scientist role developing predictive models and AI/ML solutions for financial insights. Requires Python/SAS/SQL expertise and collaboration with investment distribution teams.
Responsibilities
- Develop and refine predictive models using machine learning algorithms to inform sales and distribution strategies. Collaborate with data engineers to establish data pipelines and analytics tables. Mine large, complex datasets—including structured and unstructured data—to identify patterns, trends, and actionable insights. Design and implement new processes for data modeling and analysis. Create dashboards and visualizations to communicate insights effectively to business stakeholders. Assess the feasibility of AI/ML solutions and explore innovative data technologies. Provide recommendations and strategic insights to senior leadership to enhance market competitiveness. Work closely with investment distribution teams to deploy analytics solutions that support sales objectives. Communicate complex technical concepts in clear, accessible language. Anticipate data trends and adapt strategies accordingly. Foster collaboration across internal teams and external partners to achieve project goals. Manage ambiguity and prioritize tasks effectively in a fast-paced environment.
Requirements
- 4+ years of experience or relevant certifications in analytics, data science, or related fields. Strong proficiency in SQL and experience with Python, R, or SAS. Demonstrated expertise in data visualization tools such as PowerBI or similar. Proven ability to design and develop machine learning models and predictive algorithms. Excellent verbal and written communication skills. Strong team collaboration skills with the ability to work cross-functionally. Ability to navigate ambiguous situations and manage multiple priorities. Data-driven decision-making mindset. Nice to Have: Experience within the investment industry or financial sales sectors. Prior banking or financial services experience. Professional certification such as CFA or an advanced degree in a relevant field.
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