Apiture
Senior Data Analyst
Apiture, Wilmington, North Carolina, United States, 28412
At Apiture, our mission is to empower financial institutions to know and serve their clients with the care of a traditional community institution at the scale, speed, and efficiency required in today's digital world. With hundreds of clients throughout the U.S., we deliver comprehensive online and mobile solutions that support banks and credit unions, ranging from small community financial institutions to new, innovative direct banks.
Summary: Apiture is seeking a versatile Data Analyst to interpret complex datasets, identify trends and provide actionable insights that drive strategic decision making for Apiture and our clients.
Location (Wilmington, NC, Austin, TX, Remote): We have offices in Wilmington, NC and Austin, TX and while some positions need to be office based, we will also consider remote candidates in our preferred time zones of CST/EST.
Responsibilities:
Conduct exploratory data analysis to identify trends, patterns and anomaliesPerform deep data mining and manipulation using SQLWork with clients to understand their business needs, formulate end-to-end solutions and train them to use these solutions effectively.Deliver effective presentations of findings and recommendations by creating creative visual displays of quantitative information.Work closely with the Application Development and Data Engineering teams to operationalize and maintain customer-facing data products.Stay up to speed on new analytics trends, techniques, and technologies, and surface opportunities for their application.Become a subject matter expert for the various business areas and their strategies, processes, policies, etc to have a holistic understanding of the business and how it's reflected in the data we capture.Guiding/mentoring other analysts on best practices for analysis and data story-telling.Organically finding insights through data exploration and business knowledge even without stakeholders explicitly asking for it.Serve as an internal champion for the analytics team, including internal communication, asset creation.Requirements:
A bachelor's degree in Computer Science, Data Science, Machine Learning, Mathematics, Statistics, Economics, or other related fields with emphasis on quantitative methods and solutions.5+ years experience working in Data Science, Machine Learning, or Computer Science roles.Excellent data visualization and presentation skills using tools like Domo, PowerBI, Tableau.Ability to write (and refactor) robust code in Python and SQL employing best practice coding standards and documentation.Prior experience with data platforms like Snowflake, AWS DMS, etc.Strong people and communication skills to connect and influence both technical and non-technical audiences.Experience in defining new measures and the translation of business goals into quantitative metrics and reportingNice to Have
Experience in the banking industry.Demonstrated skills in selecting the right statistical tools given a data analysis problem.Develop, implement and improve Machine Learning algorithms to solve complex business problems.Build predictive models for forecasting, risk assessment and customer segmentationFamiliarity with designing and analyzing A/B testing and other experiment types.Demonstrated experience employing DevOps or MLOps methodologies.
Summary: Apiture is seeking a versatile Data Analyst to interpret complex datasets, identify trends and provide actionable insights that drive strategic decision making for Apiture and our clients.
Location (Wilmington, NC, Austin, TX, Remote): We have offices in Wilmington, NC and Austin, TX and while some positions need to be office based, we will also consider remote candidates in our preferred time zones of CST/EST.
Responsibilities:
Conduct exploratory data analysis to identify trends, patterns and anomaliesPerform deep data mining and manipulation using SQLWork with clients to understand their business needs, formulate end-to-end solutions and train them to use these solutions effectively.Deliver effective presentations of findings and recommendations by creating creative visual displays of quantitative information.Work closely with the Application Development and Data Engineering teams to operationalize and maintain customer-facing data products.Stay up to speed on new analytics trends, techniques, and technologies, and surface opportunities for their application.Become a subject matter expert for the various business areas and their strategies, processes, policies, etc to have a holistic understanding of the business and how it's reflected in the data we capture.Guiding/mentoring other analysts on best practices for analysis and data story-telling.Organically finding insights through data exploration and business knowledge even without stakeholders explicitly asking for it.Serve as an internal champion for the analytics team, including internal communication, asset creation.Requirements:
A bachelor's degree in Computer Science, Data Science, Machine Learning, Mathematics, Statistics, Economics, or other related fields with emphasis on quantitative methods and solutions.5+ years experience working in Data Science, Machine Learning, or Computer Science roles.Excellent data visualization and presentation skills using tools like Domo, PowerBI, Tableau.Ability to write (and refactor) robust code in Python and SQL employing best practice coding standards and documentation.Prior experience with data platforms like Snowflake, AWS DMS, etc.Strong people and communication skills to connect and influence both technical and non-technical audiences.Experience in defining new measures and the translation of business goals into quantitative metrics and reportingNice to Have
Experience in the banking industry.Demonstrated skills in selecting the right statistical tools given a data analysis problem.Develop, implement and improve Machine Learning algorithms to solve complex business problems.Build predictive models for forecasting, risk assessment and customer segmentationFamiliarity with designing and analyzing A/B testing and other experiment types.Demonstrated experience employing DevOps or MLOps methodologies.