Data Analytics Manager

Position Responsibilities

• Cook up and execute data quality standards, data protection standards, and adoption requirements.
• Support the design, development, maintenance, and evaluation of statistical and predictive models to identify historical trends and forecast future performance.
• Provide day-to-day direction and oversight for the Data Analytics team.
• Ensure accuracy of data and deliverables of reporting and comprehensive policies and processes.
• Engage with different functional teams and tools to develop and implement new predictive models and analyze their performance.
• Serve as a central coordinator for data governance, data access, and data usability for the organization.
• Cook up and streamline external data sources to eliminate redundancy and reduce expenses.
• Proactively manage the development of ROI analysis on promotional campaigns as well as credit union products and services.
• Assess the effectiveness and accuracy of all data sources and data gathering techniques for various types of analyses.
• Oversee and evaluate data being pulled into data visualization and CRM software.
• Work with other departments to identify data cleansing needs and find appropriate solutions.
• Research and develop machine learning and data analysis techniques and models using Python or other data tools.
• Oversight of the development and maintenance of dashboards for senior level executives.
• Recognize opportunities to automate processes for optimization and increased efficiency.
• Provide quality support and maintain a professional relationship with peers, management, other staff, and members through cooperation, mutual trust, and respect.
• Maintain confidentiality regarding credit union policies and procedures, member financial data, personal information, and work-related events.
• Use SQL, Tableau and other appropriate tools to interrogate data (profile, map & aggregate) to fulfill both ad-hoc and solution development requests.
• Use Python or R, develop advanced analytics techniques such as predictive modelling, retention analysis, and cluster or cohort analysis.
• As an overlay to all work, provide continual assistance with the identification, assessment, and resolution of data quality issues.
• Work closely with assigned PMO staff and Business Analysts, assist in the fulfillment of projects from planning through to implementation.
• Adhere to organization and department standards and processes such as Change Management, Information Security, and Data Governance.
• As an overlay to all work, provide continual assistance with the identification, assessment, and resolution of data quality issues.

Required Knowledge and Skills

• Demonstrated managerial skills and previous management experience preferred.
• Ability to present complex information in an understandable and compelling manner.
• Intermediate to advanced capabilities with SQL.
• Experience developing statistical models or advanced analytics with R, Python, and/or SAS.
• Practical knowledge of data in various forms (data warehouses/SQL, unstructured data environments).
• Familiarity with BI reporting tools (i.e. Tableau, Power BI or similar BI tool).
• Experience working within process management and improvement methodologies – Lean, Six Sigma, etc. and demonstrating knowledge of data governance, data quality management concepts and data quality tools.
• Understanding of Agile development methodologies, software design patterns.
• Experience in quantitative analysis and statistical modelling.
• Understanding of data infrastructure and ELT/ETL frameworks.
• Able to organize and manipulate data sets to extrapolate conclusions.
• Knowledge of and experience with software development teams, industry best practices, regulations & compliance, and quality assurance techniques.
• Able to identify and research data anomalies (e.g. mismatched records, nulls, repeating records).
• Excellent critical and analytical thinking skills coupled with strong problem-solving skills.
• Excellent task management, organizational, and communication skills with great attention to detail.
• Excellent written skills to formalize recommendations to Senior Management.
• Able to identify and research data anomalies (e.g. mismatched records, nulls, repeating records).
• Willing to learn using available resources.
• Strong interpersonal skills and ability to solicit participation and input from others.
• Experience with MS-Office with particularly strong skills in Word, Visio, and Excel.