Research Data Analyst

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Who We Are

Addepar’s purpose is to maximize the positive impact of the world’s capital. More than 700 of the world’s leading financial services firms trust Addepar to unlock the power and possibility of informed, data driven investing and advice. These family offices, wealth managers, banks and institutions use Addepar’s purpose-built SaaS platform and associated Marketplace to deliver exceptional value to their clients in a modern, scalable and secure way. 

Our clients use Addepar to manage and advise on more than $3.5 trillion in assets, and we’ve been adding more than $15 billion per week for many consecutive quarters, making us one of the fastest growing companies in fintech. Our board and investors are some of the best in the business: D1 Capital, WestCap, 8VC and Valor Equity Partners have led our last few rounds. 

We’re now expanding Addepar’s business around the globe, with clients in more than 25 countries. We’re constantly doubling down on tech- and data-fueled innovation, and our product and platform roadmap is more ambitious today than ever. We place our clients at the center of everything we do, and see a virtually unlimited set of opportunities to expand our client footprint and deepen the value we can unlock by building together. 

Addepar is a Forbes Fintech 50 company and an honored member of the CB Insights Fintech 250. Addepar embraces a global flexible workforce model with offices in Silicon Valley, New York City, Salt Lake City and Edinburgh, Scotland.

*Marketplace and brokerage services provided by Acervus Securities, Inc., an SEC registered broker‑dealer and member FINRA / SIPC.

The Role

We are currently seeking a Data Analyst to join our new Research & Insights organization. R&I is a newly launched Addepar capability that will carry out research projects on investment decision-making and deliver new research products on topics related to investing  (e.g., briefs, working papers, journal articles, models). The R&I mission is to inform wealth managers and institutional investors on new ways to improve their investment performance, by helping them augment their governance, management, operations, and processes. The goal is to utilize Addepar’s proprietary and private data (both quantitative and qualitative) to bring new and powerful insights to the world of investors. 

As a Data Analyst, you will participate in the full lifecycle of research including ideation, data set analysis, generation of analytics, prototyping, and implementing analytical tools that bring new and powerful insights to the world of investors. Successful candidates will be proven subject matter experts in data science across its full lifecycle, be practical in your approach to deploying simple vs. complex methodologies, and have demonstrated success in using data to achieve business outcomes.

  • You will report to the Head of Research Analytics and will collaborate with the entire R&I team on the collection and analysis of both quantitative and qualitative data. You will also partner with the engineering team to implement tools developed by the organization. 
  • You will be expected to be independently capable of executing a full lifecycle data science project including gathering data, data cleansing, exploration, modeling, and visualization.  You will be expected to create documentation and presentations to communicate decision-making, progress, and results with the team and other Addepar stakeholders.
  • You will proactively contribute to data quality and suggest upstream improvements that enhance the value of inputs to our analytics and models.
  • You will collaborate with engineering and other data teams at Addepar to enhance the pipeline of data used for analysis.
  • You will develop relationships across the organization to keep abreast of data engineering and architecture developments across the company that impact the R&I team.

Who You Are 

  • 4+ years of relevant work experience as a data analyst at financial services or research organization similar to this one
  • Extensive experience with Excel, Python, and SQL
  • Subject matter expertise in data science techniques and a practical approach to data analysis with the complexity of the approach matching the needs of each particular situation.
  • Familiarity with financial markets, in particular benchmarking, portfolio construction, capital flows, and alternatives is a plus
  • Experience with communicating (written and verbally) complex topics in a simple way to both technical and non-technical audiences
  • Demonstrated ability to help use data to achieve business objectives

Our Values 

  • Act Like an Owner - Think and operate with intention, purpose and care. Own outcomes.
  • Build Together - Collaborate to unlock the best solutions. Deliver lasting value. 
  • Champion Our Clients - Exceed client expectations. Our clients’ success is our success. 
  • Drive Innovation - Be bold and unconstrained in problem solving. Transform the industry. 
  • Embrace Learning - Engage our community to broaden our perspective. Bring a growth mindset. 

In addition to our core values, Addepar is proud to be an equal opportunity employer. We seek to bring together diverse ideas, experiences, skill sets, perspectives, backgrounds and identities to drive innovative solutions. We commit to promoting a welcoming environment where inclusion and belonging are held as a shared responsibility.

To ensure the health and safety of all Addepeeps and our prospective candidates, we have instituted a virtual interview and onboarding experience.

Unfortunately, at this time we cannot accept Colorado applicants.

More Information on Addepar
Addepar operates in the Analytics industry. The company is located in Mountain View, CA, New York, NY, Salt Lake City, UT and Chicago, IL. Addepar was founded in 2009. It has 850 total employees. It offers perks and benefits such as Volunteer in local community, Open door policy, Flexible work schedule, Remote work program, Mandated unconscious bias training and Diversity employee resource groups. To see all jobs at Addepar, click here.
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