Data Analyst

Responsibilities:

• Analyzes data, assesses trends and develops actionable insights and recommendations in support of business objectives.
• Trains and develops junior analysts.
• Work closely with business partners to develop data-driven insights and recommendations to improve the client experience.
• Develop and maintain dashboards and reports to track and monitor key performance indicators.
• Collaborate with cross-functional teams to develop and implement solutions to improve the client experience.
• Use statistical techniques to analyze large and complex datasets.
• Analyze customer data to uncover trends and patterns that impact the client experience.
• Collaborate with cross-functional teams to design and execute experiments that test hypotheses and measure the impact of new initiatives on customer experience and business performance.
• Communicate insights and recommendations to stakeholders across the organization, including senior management, to inform decision-making.
• Stay current with industry trends and emerging technologies related to data analytics, customer experience, and financial services.

Qualifications:

• Undergraduate degree in an analytic/quantitative field such as: Data Science, Business Analytics, Applied Mathematics, Statistics, Economics or related quantitative field of study or equivalent combination of training and experience.
• 4-6 years of relevant work experience
• Extraordinary analytical skills, coupled with the ability to form hypotheses and draw meaningful insights from disparate data sources. The ability to understand data, process it, extract value from it, visualize it and communicate insights to audiences of various backgrounds, including senior management.
• Demonstrated track record of building strong relationships across technical and non-technical employees.
• Strong command of advanced data analysis tools and software (Python, Tableau preferred), and querying languages (SQL)
• Experience working within a cloud-based, big data environment (AWS preferred)
• Highest standards of accuracy and precision; highly organized

Preferred Qualifications:

• A graduate level degree in an analytic/quantitative field such as: Data Science, Business Analytics, Applied Mathematics, Statistics, Economics or related quantitative field of study
• Experience with advanced statistical and machine-learning methods such as: regression models, propensity models, segmentation, optimization, experimental test design, time series analysis, cohort analysis, Bayesian methods, decision trees, text analysis, etc.