Senior Specialist – Advanced Analytics

Senior Specialist – Advanced Analytics

Requirements

• Advance Data-driven Decision Making: Apply advanced data and analytics methods to identify opportunities, evaluate alternatives, optimize decisions, measure impact, and share insights/recommendations for continuous improvement/transformation.
• Big Picture Strategic Ideation: Connect the dots across product families, teams, and divisions to design the analytical vision, generate roadmaps and prioritize initiatives.
• Cross-Functional Collaboration: Act as a true peer in driving strategy and roadmap, working closely with cross-functional teams to facilitate effective use of data.
• Stakeholder Management: Communicate with and manage senior stakeholder relationships to drive strategic direction and roadmap development.
• Autonomy and Proactivity: Ability to carve out your own initiatives and workplan based on department priorities, map out the course, roles and responsibilities for all supporting team members.
• Growth Mindset: Be responsible for your continuous learning. Stay on top of latest analytics and data science methods, use case and technologies to drive efficiency and impact using data.
• Executive Presence: Participate in key high-priority and strategic leadership meetings and enterprise initiative discussions to maintain a big-picture viewpoint. Articulate complex concepts to a variety of audience in a crisp and impactful fashion.
• Thought Leadership: Connect diverse ideas and/or bring structure to high impact problems for business/product. Translate complex problems into an analytical framework and lead intricate projects through from ideation to completion.
• Collaborative mentality: Delegate tasks and provide tactical and strategic guidance to peer analysts, data engineers and data scientists. Serve as the analytics expert on cross-functional teams for enterprise-wide strategic initiatives.
• Analytics and Data Science Expertise: Expertise to perform data analysis from multiple sources to surface trends and insights using advanced analytical methods. Drive innovative and sophisticated experimentation across multiple families to identify and implement innovative CX solutions.

Responsibilities

• Engages with internal partners to understand business strategy, questions, and goals. Brings structure to business requests, translates requirements into an analytical project approach, and leads complex projects through completion. Delegates tasks and provides tactical and strategic guidance to peers. Serves as the analytics expert on cross-functional teams for enterprise-wide strategic initiatives.
• Acquires and compiles structured and unstructured data and verifies its quality, accuracy, and reasonableness. Leads the development of data quality standards, and the tools and methods used to measure and improve data quality.
• Performs analyses of data from multiple sources to surface trends and insights using advanced analytical methods and machine learning. Validates analytical techniques employed by other analysts.
• Prepares and delivers expert level visualizations and internal presentations that translate analytic insights into tangible, actionable solutions for senior leader stakeholders to implement.
• Develops, owns, and manages recurring analytic or reporting processes. Demonstrates expertise in data visualization and mentors analysts on data visualization best practices.
• Develops the analytics community at Vanguard by mentoring, coaching and connecting others with resources and training. Stays abreast of emerging trends and external best practices. Participates and presents during scheduled analytics seminars.
• Participates in special projects and performs other duties as assigned.

Preferred Qualifications

• Minimum of 10 years of related work experience in advanced analytics and data science within a financial services context.
• Undergraduate degree in an analytic/quantitative field such as: Applied Mathematics, Statistics, Economics or related analytical field of study or equivalent combination of training and experience. A graduate level degree in an analytics focused field is strongly preferred.
• Extraordinary analytical skills, coupled with the ability to form hypotheses and draw meaningful insights from disparate data sources. The ability to understand data, process it, extract value from it, visualize it and communicate insights to audiences of various backgrounds, including senior management.
• Expert level skills in the following suite of data analysis tools: Data Extraction languages such as SQL. Proficiency with relational databases or Big Data platforms, Data Analysis packages (Python, R, SAS etc.) and Data Visualization packages (Tableau, etc.).
• Significant experience with advanced statistical and machine-learning methods such as: regression models, propensity models, segmentation, optimization, experimental test design, time series analysis, cohort analysis, Bayesian methods, decision trees, text analysis.