Data Scientist

New York City
Business Intelligence
Full Time
Founded in 2015, Even Financial is a B2B2C fintech company that is transforming the way financial institutions find and connect with consumers. By seamlessly connecting financial institutions (including American Express, Goldman Sachs, and SoFi) and channel partners (such as TransUnion, The Smart Wallet, and The Penny Hoarder) via its industry-leading API, Even turns any consumer touchpoint into an ROI-driven, programmatic acquisition source with full compliance and security across loans, savings, credit cards, and more. Even is backed by leading VCs and financial services firms including American Express Ventures, Citi Ventures, F-Prime Capital (Fidelity), Goldman Sachs, LendingClub, and MassMutual Ventures.

Even strives to foster an environment whereby all employees, across all functions and levels, are positioned for maximum personal and professional growth. We as a team have an ownership mentality, and everyone is all in to help Even achieve our vision and reach our enormous potential. Our values include being empowered (take initiative - don’t wait around for someone to tell you what to do), empirical (explore and iterate, relying on observation and experience), transparent (be helpful, straightforward and honest with customers and coworkers), and fearless (take bold risks and commit to a solutions-oriented approach).

About you.
We are looking for a Data Scientist to join the Data Science team. You will join a fast paced team, drive data science excellence at Even, and will support the inception, enhancement, development and implementation of new and existing data science models. 

Some Of The Questions We Explore Are:

    • How can we rank financial product offers for each consumer we see given a point in time need?
    • How can we integrate with third party data sources to enhance our recommendation models?
    • How can we best mix active and passive signals to maximize click through rates?
    • How do we optimize against the different data flows we have, given our open API?
    • How do we build a strong data science process that effectively documents, experiments with and monitors model performance?

Day to Day:

    • Work on different elements of Learning to Rank problems, such as constructing ranking experiments and measuring their results
    • Analyze, develop, test, and introduce new features and signals for our ranking and filtering systems via analysis of historical consumer data, third party data sources, and various other ML techniques
    • Work with the team to build timelines and goals for each experiment or analysis, and partner with cross functional teams (partner solutions, engineering, product, business intelligence) to roll data science outputs into production
    • Build comprehensive dashboarding and simulation systems to test models offline before they are released to production, as well as to monitor their performance once they are online
    • Produce documentation that captures experiments or analyses in detail across the entire data science lifecycle (research to results)
    • Develop, document, and implement processes to help the team to scale
    • Work on ad hoc analyses related to business requirements
    • Collaborate with teammates in an agile, high velocity environment with a focus on meeting business needs
    • Work with languages such as Scala, Python, SQL and have familiarity with AWS redshift or similar data warehousing.

Proficiencies:

    • Business acumen and communication skills (ability to communicate business value and impact), creative problem-solving and intellectual curiosity
    • Ability to work well in a team and openly collaborate with a focus on executing fast
    • Ability to decompose large, complex problems into smaller actionable parts
    • Experience with pragmatic statistical analysis in a workplace setting
    • Experience with data science models and testing and building them from scratch (e.g. logistic, tree-based models)
    • High proficiency in python and SQL
    • BA/BS in Computer Science, Math/Finance, Physics, Applied Economics, Statistics or other technical field preferred or relevant experience (3+ years)
    • Experience analyzing and computing data at scale with tools such as Spark, MapReduce, Hive, Presto, Redshift, etc. preferred
    • You have a sense of humor and want to join a fun dynamic environment where we are building things from the ground up!
Full time employees are eligible for the following benefits:
·  A comprehensive medical/dental/vision package provided through Empire Blue Cross Blue Shield.  Life and disability insurance are also included. 
·   Enrollment in our 401K plans.  Once you are enrolled in the plan, you can change your contributions rate or opt out at any time. 
·  Stock option program
·  Eight company paid holidays for the 2019 calendar year. 
·  Paid time off (PTO) is uncapped, should it be in accordance with the Company’s policy, which will be outlined during New Hire Orientation.
 ·   A subsidized gym membership with ClassPass