Senior Data Scientist

Company details

WalletHub, the #1 Personal Finance App in the US and one of Forbes' Top 100 Best StartUp Employers for both 2020 and 2021, is seeking hardworking, like-minded individuals to help us disrupt personal finance and make a tangible difference in people's everyday lives. We're looking for a highly skilled and motivated Senior 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!

Responsibilities

• 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

Requirements

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

Our Offer

• 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)

Notes

• 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 (8am - 7pm ET, including 1 hour break).
• Although we appreciate your interest in working with us, due to the high number of applications we receive, we will only be able to respond to successful applicants.