Senior Data Analyst

Apiture - Wilmington, NC

Full-time - Mid Level

Wilmington, NC

11-50 employees

Professional, Scientific, and Technical Services

About the position

Apiture is seeking a versatile Senior Data Analyst to interpret complex datasets, identify trends, and provide actionable insights that drive strategic decision-making for the company and its clients. This role involves conducting exploratory data analysis, collaborating with clients to understand their business needs, and operationalizing customer-facing data products. The analyst will also mentor other analysts and stay updated on analytics trends and technologies.

Responsibilities

• Conduct exploratory data analysis to identify trends, patterns, and anomalies.
• Perform deep data mining and manipulation using SQL.
• Work 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.
• Be a subject matter expert for various business areas and their strategies, processes, policies, etc.
• Guide and mentor other analysts on best practices for analysis and data storytelling.
• Organically find 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 and 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 reporting.

Nice-to-haves

• 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 segmentation.
• Familiarity with designing and analyzing A/B testing and other experiment types.
• Demonstrated experience employing DevOps or MLOps methodologies.