CFRA’s Quantitative Research Team generates independent insights and information designed to provide actionable analytics to make better investment and business decisions. CFRA is committed to being the world's leading independent investment research firm with ~90 global analysts, authoring in-depth qualitative research on 1,600+ companies as well as quantitative company research on 20,000+ global companies. As a Data Scientist you will work as part of a team researching data-based products for the wealth management industry. The research is integrated as part of CFRA’s flagship products and research reports. We are looking for an individual who possesses strong technical skills and loves to work on the latest in AI, Machine Learning, Data Science and Data Visualization technologies. The ideal candidate has a passion for solving business problems with technology and can effectively communicate with stakeholders. We are looking for candidates that value collaboration with colleagues and having an immediate, tangible impact for a leading global independent financial insights and information company.
Key Responsibilities
Support methodology development and execution of various data analytics models and dashboards in financial analytics domains.
Leverage structured and unstructured datasets to build and maintain quantitative frameworks.
Analyze data for trends and patterns, understanding insight from data with a unbiassed mindset.
Implement analytical methodologies to help solve various problems related to the financial industry.
Develop and utilize algorithms to perform back-testing and error analysis to improve model uniformity and accuracy.
Close collaboration with software developers and machine learning engineers in the implementation of analytical models into production or commercialization.
Strong problem-solving skills with an emphasis on product development.
Communicate your findings to both technical and non-technical stakeholders.
Skills, Knowledge, and Expertise
Required Qualifications
Degree in a highly quantitative field: Computer Science, Machine Learning, Statistics, Mathematics, etc.
4-6 years of working experience with data related positions, data querying, data analysis, as well as ability to query/explore/link datasets.
Proficiency with data mining, knowledge of probability theory and advanced statistical techniques.
Experience with regression analysis (beyond linear regression), supervised learning, unsupervised learning, or time-series analysis.
Experience with scientific scripting languages (e.g., Python, R, etc.).
Experience accessing and manipulating data in SQL database environments.
Excellent communication and presentation skills. The candidate must be able to effectively communicate with management, reservoir characterization teams, engineering teams, clients, and other stake holders.
Preferred Qualifications
Working knowledge of AWS related toolkits: Lambda, Glue, Batch, etc.
Working knowledge of software development lifecycle (SDLC) methodologies like Agile/Scrum.
Working knowledge of code pipelines such as Jenkins, Azure DevOps, or AWS CodePipline.
