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This position has been classified as an Access Person, which will require the reporting of your personal securities transactions.
We are an equal opportunity/affirmative action employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender identity or expression, sexual orientation, national origin, disability, age or status as a protected veteran, or any other characteristic protected by law.
The Planning Algorithms team offers a unique opportunity within the Learnvest organization. At the heart of the acquisition in 2015, our planning software has been used to deliver thousands of financial plans to households across the U.S. We are actively scaling our tools to be used by Northwestern Mutual's X+ field representatives who deliver over Y financial plans per year. Our representatives work with a diversity of households with a wide range of needs, and we are looking for talented engineers to help us expand our financial modeling capabilities to meet them. As a platform team, we provide the simulation architecture that enables planners to create robust models of their clients' lives and deliver advice to help them reach their financial goals.
Members of our team generally follow one of two tracks. We expect all of our developers to gain exposure to both, though most developers will specialize in one or the other.
Core Simulation Engine
This group is responsible for providing a robust simulation engine that our Scenarios and Optimizations team uses to rapidly prototype scenarios reflecting the impacts of various planning strategies. Responsibilities include:
Modeling cashflow trajectories and providing an API for allocating surplus and covering deficits
Modeling various financial instruments including a range of debt types, pensions, annuities and various securities
Simulating portfolio growth and distribution strategies
Working with data scientists to formalize predictive models
Working with our architecture team to meet our scaling needs
Scenarios and Optimizations
This group is responsible for leveraging the core simulation engine to build scenarios our interface teams use to assist the planner in making recommendations for their clients and demonstrating the benefit of that advice. Responsibilities include:
Designing and implementing optimization techniques for allocation and distribution strategies
Build an array of what-if scenarios to model the impact of client behavior
Evaluate planner-driven and algorithmically generated recommendations.
Analyze the impact of changes to our advice on our client population
Support a GraphQL based API to make our simulation data widely available to partner teams
A strong background in engineering complex software systems OR
A strong background in financial modeling with some professional programming experience
Candidates with less finance experience will be expected to go through a rigorous onboarding process to learn those skills
Willingness to embrace functional programming paradigms (and Scala)
Finally, we do not believe that whiteboarding problems or brain teasers are at all indicative of a candidate's ability to perform well. Instead, we prefer candidates to demonstrate a capacity for the type of work they would actually complete. Candidates will be asked to perform a challenging, but fair coding assignment, with an emphasis on design skills and an ability to work with financial subject matter. Candidates with a background in finance can expect to spend 3-4 hours on the assignment. Candidates without that experience should factor in additional time to research and internalize the material.
Req ID: 25597 Position Type: Regular Full Time Education Experience: Bachelor's Desired Employment Experience: 3-5 years Licenses/Certifications: Not Applicable FLSA Status: Exempt Posting Date: 07/11/2019 - provided by Dice Associated topics: application developer, architect, c#, design, java, matlab, php, programming, project architect, software architect
* The salary listed in the header is an estimate based on salary data for similar jobs in the same area. Salary or compensation data found in the job description is accurate.