Data and Analytics Specialist

Capital Group•Los Angeles, CA

1d•Hybrid

About The Position

As a Data and Analytics Specialist you will partner with business, data domain owners/stewards, and technology teams to define and deliver data products, analytics, and reporting that improve decision-making, strengthen data domain maturity, and measurably advance business outcomes. At Capital Group, the success of the people who invest with us depends on the people in whom we invest. That’s why we offer a culture, compensation and opportunities that empower our associates to build successful and prosperous careers. Through nine decades, our goal has been to improve people’s lives through successful investing. We know that our history is a testament to the strength of the people we hire. More than 9,000 associates in 30+ offices around the world help our clients and each other grow and thrive every day.

Requirements

Partner with business, data domain owners/stewards, and technology teams to define and deliver data products, analytics, and reporting that improve decision-making, strengthen data domain maturity, and measurably advance business outcomes.
Define and drive a data product vision, strategy, and roadmap aligned to business priorities, value, and delivery feasibility.
Lead end-to-end data product lifecycle practices (intake, discovery, prioritization, delivery, adoption, measurement, and retirement).
Partner with data domain owners and stewards to assess current-state maturity, define target maturity, and execute a plan to close gaps.
Build strong partnerships with business units to understand decision needs and translate them into clear data and insight requirements.
Guide teams to collect, analyze, and interpret data to produce evidence-based recommendations and actionable insights.
Coach others in communicating complex findings through clear narratives and effective data visualizations for stakeholders.
Lead comprehensive data and business process analysis to solve complex problems across multiple stakeholders and capabilities.
Oversee the design, build, and maintenance of analytics and reporting solutions that enable scalable, trusted insights.
Stay current on emerging technologies, industry trends, and best practices and apply them to improve standards and delivery.
Champion data strategy and literacy by creating roadmaps, driving adoption and training plans, and tracking success metrics.
Lead and develop talent by setting goals, mentoring and coaching, managing performance, and supporting hiring efforts.
Lead with an AI-ready mindset, identifying opportunities to embed AI and automation into data products, workflows, and decision-making.

Responsibilities

Define and drive a data product vision, strategy, and roadmap aligned to business priorities, value, and delivery feasibility.
Lead end-to-end data product lifecycle practices (intake, discovery, prioritization, delivery, adoption, measurement, and retirement).
Partner with data domain owners and stewards to assess current-state maturity, define target maturity, and execute a plan to close gaps.
Build strong partnerships with business units to understand decision needs and translate them into clear data and insight requirements.
Guide teams to collect, analyze, and interpret data to produce evidence-based recommendations and actionable insights.
Coach others in communicating complex findings through clear narratives and effective data visualizations for stakeholders.
Lead comprehensive data and business process analysis to solve complex problems across multiple stakeholders and capabilities.
Oversee the design, build, and maintenance of analytics and reporting solutions that enable scalable, trusted insights.
Stay current on emerging technologies, industry trends, and best practices and apply them to improve standards and delivery.
Champion data strategy and literacy by creating roadmaps, driving adoption and training plans, and tracking success metrics.
Lead and develop talent by setting goals, mentoring and coaching, managing performance, and supporting hiring efforts.
Lead with an AI-ready mindset, identifying opportunities to embed AI and automation into data products, workflows, and decision-making.