The role is responsible for providing support to the Data Science - Investment Research team at Columbia Threadneedle Investments, an Ameriprise Financial company. The role is to identify opportunities to apply Analytics to improve the analyst's recommendation, operational efficiency and effective delivery. The individual will also support the development, articulation, and enablement of Columbia Threadneedle Research initiative and firm-wide strategic vision.Key ResponsibilitiesDevelop Jupyter notebooks and dashboards to analyze economic, consumer and other investment research related data to help investment analysts construct investment recommendationsHelp develop, alongside technology teams, processes to on-board and prepare datasets for further analysisMaintain code and processes that are used within the investment research teamDevelopment and execution of reports for program tracking, model validation, and other information-based solutions supportPropose and manage independent and group research projectsDevelop data pipelines, maintenance of data and data system integrity to both extract information and provide insights, including automation, data sourcing, architecture, and systems used to collect dataCollaborate with other investment analysts to contribute to help develop analytical applications and analyze investment research related data. Should be able to confidently present solutions/proposalsUse best practices and knowledge of internal or external business issues to improve products or services. Develops competence by performing structured documentation, automation, etc.Required QualificationsBachelor’s degree in Engineering/Computer Science or any related fields and/or MBA (Finance) and/or pursuing CFA3 - 5 years of relevant experience in data analytics for a global financial services / asset management firmOutstanding quantitative/analytical/statistical skills and the ability to manage and interpret large amounts of data. Able to create full stack solutionsExceptional communication skills (needs to effectively work and stay in touch with global colleagues across different business units)Proficient in programming in Python and good knowledge of scientific/analytical libraries such as numpy, scipy, pandas and plotly dashExcellent organizational and project management skills to track and manage multiple deliverables…