Platform Product Analyst

Employment Type: [Not Specified] Location Type: [Not Specified] Salary: [Not Specified]

Who We Are

Addepar is a global technology and data company that helps investment professionals provide the most informed, precise guidance for their clients. Hundreds of thousands of users have entrusted Addepar to empower smarter investment decisions and better advice over the last decade. With client presence in more than 50 countries, Addepar’s platform aggregates portfolio, market and client data for over $7 trillion in assets. Addepar’s open platform integrates with more than 100 software, data and services partners to deliver a complete solution for a wide range of firms and use cases. Addepar embraces a global flexible workforce model with offices in New York City, Salt Lake City, Chicago, London, Edinburgh, Pune, and Dubai.

The Role

We are currently seeking a Platform Product Analyst to join our Data Enablement team! This is an exciting opportunity for a junior product professional to contribute directly to the foundational Data Platform driving Addepar's global expansion strategy.

The Data Enablement team’s mandate is to empower Addepar's internal and external data consumers with a scalable, global operating platform. You will provide crucial product management input to Engineering teams, helping them deliver solutions that directly enable our global expansion strategy across new market segments and client personas.

What You’ll Do

As a Platform Product Analyst, you will play a key supporting role in the evolution of Addepar's Data Platform:

• Support Product Development: Assist Product Managers and Engineering teams in delivering high-quality, timely, and reliable data workflow solutions.
• Inform the Strategic Roadmap: Gather insights and data to support the prioritization of new features and platform capabilities. You will help the team make decisions that align with Addepar’s north star outcomes.
• Champion the Platform Consumer: Mentor under senior product managers to develop a deep understanding of the platform's "consumers," including our Core Product, AI, and Workflow platform teams. You will apply these insights to help deliver foundational "building blocks" that empower these teams to build new client offerings with greater velocity.
• Document & Define: Use your growing understanding of our ecosystem to describe and diagram key workflows. You will contribute to writing clear requirements for transforming raw data into functional content on our platform.
• Investigate Issues: Assist in investigating issues raised by clients or partner teams, working with development teams to refine and support the implementation of fixes.
• Agile Participation: Actively participate in agile ceremonies (e.g., stand-ups, sprint reviews, retrospectives), helping to ensure smooth team operations.

Who You Are

You are an emerging product professional with a strong interest in data, platforms, and operational efficiency within the financial technology space.

• Experience: Relevant work experience or a strong academic background combined with internships/entry-level roles that demonstrate an aptitude for product analysis, data, or user workflows.
• Domain Interest: A foundational understanding of data processing concepts, SQL, and an eagerness to learn about financial products. Prior exposure to Python and Databricks is a plus.
• Agile Mindset: Practical knowledge of agile principles; a willingness to experiment with project approaches and learn how to guide teams towards effective activities and processes.
• Analytical Skills: Ability to analyze information, identify problems, and contribute to developing solutions.
• Collaboration: Ability to partner effectively with a variety of stakeholders (from highly technical engineers to non-technical business colleagues) and thrive in a cross-functional setting.
• Problem-Solver: A confident and positive attitude with low ego; high degree of ingenuity, resourcefulness, and problem-solving skills; ability to work within ambiguity and learn quickly.
• Communication: [Not Specified]