WalletHub · Jun 27th 2019
WalletHub is one of the leading personal finance destinations in the US and rapidly growing. We're looking for a highly experienced and motivated Data Scientist for a full-time, permanent position.
The main objective of the Data Science Team is to improve WalletHub's services and core product. This has a direct impact on the overall user experience.
Making the right personal finance decisions by sifting through vast amounts of available information can be a daunting task for almost anyone. This is because a large number of interrelated factors need to be taken into account when making such decisions.
By designing and constructing data-driven models, the Data Science Team is able to provide our users with indispensable knowledge and meaningful advice on how they can achieve their personal finance goals.
Such goals include:
Selecting the best financial products for your needs
Taking the right actions to improve your credit score
Anticipate your future financial health based on your current financial status and history
With these goals in mind, our Data Scientists use the latest cloud technologies and machine learning tools in order to exploit the potential of data analytics. We always have new and interesting projects on the horizon that aim to help our users reach their personal finance aspirations!
You are the ideal candidate for this job if you have:
At least 8 years experience in Java, Spring and MySQL (or any relational database) and Python
At least 5 years of experience as a Data Scientist.
Experience with databases (including NoSQL)
Experience in machine learning frameworks and libraries
Supervised and Unsupervised learning
Machine learning concepts and techniques: Regularization, Boosting, Random Forests, Decision Trees, Bayesian models, Neural networks, Support Vector Machines (SVM)
Experience with the whole ETL data cycle (extract, validate, transform, clean, aggregate, audit, archive)
Computer Science or Mathematics or Physics degree
Excellent communication and analytical skills
Willingness to work hard (50 hrs per week)
Very good English
Nice to have but not required
Experience with Apache Spark
Natural Language Processing (tokenization, tagging, sentiment analysis, entity recognition, summarization)
R programming language
Modeling complex problems, discovering insights and identifying opportunities through the use of statistical, algorithmic, mining and visualization techniques
Participating in the areas of architecture, design, implementation, and testing
Proposing innovative ways to look at problems by using data mining approaches on the set of information available
Designing experiments, testing hypotheses, and building models
Conducting advanced data analysis and designing highly complex algorithm
Applying advanced statistical and predictive modeling techniques to build, maintain, and improve on multiple real-time decision systems
Very competitive salary based on prior experience and qualifications
Potential for stock options after the first year
Raise and advancement opportunities based on periodic evaluations
Visa sponsorship (if working from outside the US, sponsorship can be granted after 18 months with the company, based on performance).
Health benefits (in case you will be working from our office in Washington DC)
This position does not have a location requirement and can be performed either remotely (including from outside the U.S.) or from WalletHub’s offices in downtown Washington DC.
If you're intending to work from outside the US please be aware this position entails working at least 50 hour per week and requires an overlap with EST business hours.
More about WalletHub
WalletHub is a high-growth fintech company based in Washington, DC that is looking for talented, hard-working individuals to help us reshape personal finance. More specifically, we are harnessing the power of data analytics and artificial intelligence to build the brain of a smart financial advisor, whose services we’re offering to everyone for free. The WalletHub brain enables users to make better financial decisions in a fraction of the time with three unique features:
1) Customized Credit-Improvement Tips: WalletHub identifies improvement opportunities and guides you through the necessary corrections.
2) Personalized Money-Saving Advice: WalletHub’s savings brain constantly scours the market for load-lightening opportunities, bringing you only the best deals.
3) Wallet Surveillance: Personal finance isn’t as scary with 24/7 credit monitoring providing backup, notifying you of important credit-report changes.
In addition to the valuable intelligence the brain provides, WalletHub is the first and only service to offer free credit scores and full credit reports that are updated on a daily basis absent of user interaction, rather than weekly or monthly and only when a user logs in. Some other services hang their hats on free credit scores and reports, yet they’re still inferior to what WalletHub considers minor pieces to a much larger puzzle.
How to Apply
To get our attention, all you need to do is send us a resume. If we believe that you will be a good match, we'll contact you to arrange the next steps. You can apply directly on Stackoverflow or email your application to firstname.lastname@example.org