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/Machine Learning 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/Machine Learning Engineers 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!

Expected work schedule is 50 hours/week, Monday to Friday. In case you will be working from outside the US, please be aware this position requires an overlap with EST business hours.

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

Qualifications

You are the ideal candidate for this job if you have:

• At least 4 years experience in Python and MySQL (or any relational database)
• Min. 2 years of experience as a Data Scientist
• Experience with databases
• Experience in machine learning frameworks and libraries
• 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)