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Fidelity Investments

Senior manager data

Fidelity Investments, Boston, Massachusetts, us, 02298


Job Description:Position Description:Builds data platforms using programming languages -- SQL, Python, and R. Designs and develops dashboards and reports using Business Intelligence (BI) visualization tools such as Adobe, Google analytics, Qlik, SQL, Tableau. Develops and leads data and hypothesis driven initiatives by using data, analytics, engineering, data science, marketing, and product development strategies to optimize and personalize user experience. Delivers insights from data to a broad audience in a simple, clear, and actionable way. Uses industry-leading analytics approaches including database analytics, digital analytics, experimentation or A/B testing, data visualization, and tools.Primary Responsibilities:Codes within data technologies and languages SQL, Python, and R.Translates business needs into a hypothesis that can be validated via experimentation or advanced data analysis to inform critical business decisions.Engages in customer-focused, cross-functional collaboration across the organization.Formulates disparate data points from multiple sources -- customer attributes and behaviors, transactional history, call transcripts, digital activity, and business financials -- into unified data for optimizing customer experience.Develops learning agendas and tests experimental designs, sampling techniques, and analytical methods.Analyzes and interprets statistical data to identify significant differences in relationships among information sources.Develops and applies mathematical or statistical modelling theories or methods to collect, organize, interpret, and summarize numerical data to provide usable information.Ability to use data to formulate KPIs and design a compelling story for the business to make an informed decision.Education and Experience:Bachelor's degree (or foreign education equivalent) in Computer Science, Engineering, Information Technology, Information Systems, Mathematics, Physics, or a closely related field and five (5) years of experience as a Senior Manager, Data Analytics and Insights (or closely related occupation) performing statistical analysis, and data extraction, transformation, and summarization to support and inform marketing strategies within the financial services industry.Or, alternatively, Master's degree (or foreign education equivalent) in Computer Science, Engineering, Information Technology, Information Systems, Mathematics, Physics, or a closely related field and three (3) years of experience as a Senior Manager, Data Analytics and Insights (or closely related occupation) performing statistical analysis, and data extraction, transformation, and summarization to support and inform marketing strategies within the financial services industry.Skills and Knowledge:Candidate must also possess:Demonstrated Expertise ("DE") scoping out data availability from sources and extracting marketing, sales, finance, and customer data for analysis, using unstructured, semi-structured, and structured databases Snowflake, Amazon Web Services (AWS) Athena, and Oracle SQL; Preparing data for analytics by integrating data across systems using data wrangling techniques to develop an analytical roadmap.DE acting as a member of an analytics team responsible for performing data modeling on raw data to create programmatic scripts that extract, transform, wrangle, and manipulate data, using SQL, Python, R, or MS Excel; performing advanced analytics techniques—statistical or predictive modelling (machine learning algorithms) to implement novel business solutions using tools like Applied Predictive Technologies (APT).DE leveraging analytical findings to develop key performance indicators (KPIs) and creating interactive business results dashboards to present actionable insights or recommendations to the senior management in a conceivable format using BI tools -- Tableau, Power BI, and Qlik; collaborating with cross-functional teams in an agile environment to formulate hypotheses by translating high-level business problems into more specific questions which can be answered through data analyses and prioritizing, sequencing, documenting the steps involved using tools such as JIRA, Confluence, and MURAL.DE designing and implementing digital measurement strategies, reporting and analytics to track customer journey/pathing metrics and interactions; proposing ideas to add or modify webpage features to improve customer digital experiences using A/B testing or experimentation -- to drive business decisions and recommendations using Adobe Analytics and Google Analytics.

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