Core Responsibilities:
Work closely with business partners to develop data-driven insights and recommendations to improve the client experience.
Develop and maintain dashboards and reports to track and monitor key performance indicators.
Collaborate with cross-functional teams to develop and implement solutions to improve the client experience.
Use statistical techniques to analyze large and complex datasets.
Analyze customer data to uncover trends and patterns that impact the client experience
Collaborate with cross-functional teams to design and execute experiments that test hypotheses and measure the impact of new initiatives on customer experience and business performance
Communicate insights and recommendations to stakeholders across the organization, including senior management, to inform decision-making
Stay current with industry trends and emerging technologies related to data analytics, customer experience, and financial services
Qualifications:
Undergraduate degree in an analytic/quantitative field such as: Data Science, Business Analytics, Applied Mathematics, Statistics, Economics or related quantitative field of study or equivalent combination of training and experience.
7+ years of relevant work experience
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
Demonstrated track record of building strong relationships across technical and non-technical crew
Strong command of advanced data analysis tools and software (Python, Tableau preferred), and querying languages (SQL)
Experience working within a cloud-based, big data environment (AWS preferred)
Highest standards of accuracy and precision; highly organized
Preferred Qualifications:
A graduate level degree in an analytic/quantitative field such as: Data Science, Business Analytics, Applied Mathematics, Statistics, Economics or related quantitative field of study
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, etc.
Special Factors
Sponsorship
Vanguard is not offering visa sponsorship for this position.About Vanguard
At Vanguard, we don't just have a mission—we're on a mission.
To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.
How We Work
Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.
Top Skills
What We Do
We are a community of 30 million who think – and feel – differently about investing. Together, we’re changing the way the world invests.
Since our founding in 1975, helping our investors achieve their goals is our sole reason for existence. With no other parties to answer to and therefore no conflicting loyalties, we make every decision—like keeping investing costs as low as possible—with only your needs in mind.
Vanguard is one of the world's largest investment companies, offering a large selection of high-quality low-cost mutual funds, ETFs, advice, and related services. Individual and institutional investors, financial professionals, and plan sponsors can benefit from the size, stability, and experience Vanguard offers. As of April 30, 2019, we managed more than $5.6 trillion in global assets. In addition, we have 189 funds in the United States and 225 funds in global markets.
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