Twine is an SF (FiDi)-based startup unit within John Hancock / Manulife Financial – a Fortune 500 global financial services company with over $1 trillion in assets. Operating from San Francisco, the team applies data-driven agile design and development practices in building a distinctive personal finance app that makes it easy to save money toward critical goals.
Since hitting the App Store, Twine has been featured in ‘Apps We Love’ and as the ‘App of the Day’ three times, maintaining a 4.6+ rating with thousands of reviews and hundreds of thousands of installs.
The team is now refining its predictive features and enriching its investment analytics to support users in saving and building wealth automatically – looking to help millions of families to achieve secure financial lives.
About the role
As an Investment Analyst, you’ll shape all aspects of Twine investment offerings, touching everything from portfolio construction and automated investment management to predictive user advice.
You’ll own specifications for essential high-impact user-facing features and work closely with product, engineering, design, operations and compliance teams to implement your vision.
Building on the existing foundations of the product, you’ll extend and optimize existing functionality (for example, enhancing projection models and Monte Carlo simulations), while driving greenfield initiatives from conception to product launch.
Along the way, you can draw on rich sources of user account and behavioral data – including collected Twine user in-app activity, account-linked events, aggregated financial balances, marketing metadata, user surveys, and more.
You’ll report to Twine’s co-founder and Head of Behavioral Finance, working closely with Twine’s CEO, Lead Data Scientist and other stellar team contributors, as well as other senior executives from John Hancock / Manulife.
- Develop and maintain models, simulations and algorithms that serve as the foundations of Twine investment offerings
- Guide investment-related product features with analysis and feature specifications
- Support engineering and product teams implementing investment related features with feedback, test frameworks and documentation
- Manage investment risks while making equity returns accessible for users by steering prudent glidepath portfolio construction
- Act as an investment domain expert alongside the Twine data team – collaborating to implement effective in-app predictive guidance
- Lead team in developing investment-related KPIs and performance benchmarks
- Advise Twine data engineers developing pipelines to enrich understanding of user investment behavior and optimize guidance