Data Scientist

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Apache Hadoop, Scala Programming, Machine learning techniques, Data science techniques, PyTorch, TensorFlow, MapReduce, R Programming

Job Description

We are looking to hire a data scientist with that rare combination of strong programming skills, database expertise, and graduate level training in advanced statistics. Any experience with financial data is definitely a plus.

You will work with our data science group to analyze complex financial data and generate predictive models that will have international impact. You will help to create an optimal data environment that is conducive to creating such models quickly and efficiently. You should be a flexible thinker with an ability to both come up with creative, actionable ideas of your own and successfully and efficiently implement the ideas of others. A successful candidate will help our growing team’s efforts to improve and develop our market-leading products.

RESPONSIBILITIES

• Prepare raw data for use in analysis and modeling
• Perform a wide variety of exploratory data analyses
• Design and execute appropriate statistical analyses
• Assist with building descriptive, causal, and predictive models with complex financial data
• Develop prototypes for visualizations and model application interfaces
• Apply supervised and unsupervised machine learning methods to a variety of finance and accounting operations
• Validate and ensure the ongoing reliability of models and applications
• Interact regularly with a variety of database types and environments
• Work in AWS and Azure platforms
• R is the preferred language to code in although ability to adapt to any language is ideal
• Work both independently and with team members
• Work closely with a small R&D team, data engineers & analysts

QUALIFICATIONS

• Extensive experience solving analytical problems using quantitative approaches
• Extensive experience with methods of supervised and unsupervised machine learning, especially multivariate regression, classification, clustering, principal components analysis, factor analysis, causal modelling, structural equation modelling, and time series analysis
• Masters or PHD level training in statistics from a quantitative field is a must
• Experience manipulating and analyzing complex data in R, Python, or SAS with the ability to adapt to different environments as needed
• A strong passion for empirical research and for answering hard questions with data.
• A flexible analytic approach that allows for results at varying levels of precision.
• Ability to communicate complex quantitative concepts in a clear, precise, and actionable manner.
• Expertise with relational databases and SQL
• Strong programming background, ideally in C#/.NET
• Experience with financial data and relevant formats a plus
• MA/MS or greater in a quantitative scientific research discipline
• Strong writing and verbal skills – able to explain complex concepts in plain language

PHYSICAL REQUIREMENTS

Work is primarily sedentary in nature; no special demands required.