Raymond James
Data Scientist Office and Procurement Services
Raymond James, St. Petersburg, Florida, United States, 33739
Data Scientist Office and Procurement Services
Join to apply for the
Data Scientist Office and Procurement Services
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Raymond James . Responsibilities
Work with business partners to define use cases for statistical and advanced analytics to enhance or create new O&PS processes. Create detailed business requirements for functional and non-functional capabilities. Prioritize business and information needs with management. Develop data collection strategies across systems to ensure data quality: collect, clean, transform, analyze data as needed. Utilize primary and secondary data sources; maintain databases and data systems. Profile data sources using SQL and other tools to support data quality and BI efforts. Identify and interpret trends in complex data sets; prepare inventories for machine learning development. Perform additional duties as assigned. Apply data governance concepts within financial services. Understand ETL and data flow principles. Design data models, develop databases, and use data mining and segmentation techniques. Employ statistical methods, including hypothesis testing. Apply machine learning and data science techniques. Use Python programming for data analysis. Create data visualizations with tools like Qlik Sense and Tableau. Qualifications
Bachelor’s in Applied Mathematics or related field. 3-6 years of relevant experience. Knowledge of financial services industry preferred. Skills
Data retrieval, blending, and analysis using tools like Alteryx. Scripting skills in Python, R, SQL. Building understandable and valuable models. Creating dashboards from multiple data sources. Proficiency with report writing and visualization tools. Abilities
Focus on client needs, identify issues, and suggest solutions. Communicate effectively to technical and non-technical audiences. Challenge conventional thinking and collaborate with stakeholders. Make pragmatic decisions based on available data and risks. Stay current with data science trends. Build collaborative relationships and deliver on schedule. Additional Information
Travel less than 25%. Hybrid work style. Commitment to diversity and equal opportunity.
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Join to apply for the
Data Scientist Office and Procurement Services
role at
Raymond James . Responsibilities
Work with business partners to define use cases for statistical and advanced analytics to enhance or create new O&PS processes. Create detailed business requirements for functional and non-functional capabilities. Prioritize business and information needs with management. Develop data collection strategies across systems to ensure data quality: collect, clean, transform, analyze data as needed. Utilize primary and secondary data sources; maintain databases and data systems. Profile data sources using SQL and other tools to support data quality and BI efforts. Identify and interpret trends in complex data sets; prepare inventories for machine learning development. Perform additional duties as assigned. Apply data governance concepts within financial services. Understand ETL and data flow principles. Design data models, develop databases, and use data mining and segmentation techniques. Employ statistical methods, including hypothesis testing. Apply machine learning and data science techniques. Use Python programming for data analysis. Create data visualizations with tools like Qlik Sense and Tableau. Qualifications
Bachelor’s in Applied Mathematics or related field. 3-6 years of relevant experience. Knowledge of financial services industry preferred. Skills
Data retrieval, blending, and analysis using tools like Alteryx. Scripting skills in Python, R, SQL. Building understandable and valuable models. Creating dashboards from multiple data sources. Proficiency with report writing and visualization tools. Abilities
Focus on client needs, identify issues, and suggest solutions. Communicate effectively to technical and non-technical audiences. Challenge conventional thinking and collaborate with stakeholders. Make pragmatic decisions based on available data and risks. Stay current with data science trends. Build collaborative relationships and deliver on schedule. Additional Information
Travel less than 25%. Hybrid work style. Commitment to diversity and equal opportunity.
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