Lead Business Analyst

2 weeks ago


San Francisco, California, United States First Citizens Full time
Overview

This position operates in a hybrid environment, requiring work both in-office and remotely. The role demands a high level of analytical expertise and complexity in data interpretation. It involves assessing various factors that influence business profitability, growth, and operational efficiency, while supporting strategic initiatives to tackle identified challenges. The analyst will evaluate existing practices, gather information on industry trends, and develop specifications to bolster business objectives. Additionally, the role includes the development and implementation of process enhancements and participation in specialized analytical projects and advanced reporting.

Responsibilities

The Digital Analytics team is part of the Global Digital Services product organization at First Citizens. We are committed to establishing a reliable analytics team that delivers timely and actionable insights to product managers, enabling them to understand their digital users, identify opportunities, enhance digital experiences, and build a premier digital platform.

Job Summary:
As a Senior Business Analyst, you will engage in high-level data analysis and complexity. Your responsibilities will include translating business inquiries into analytical tasks, collaborating with internal subject matter experts (SMEs), constructing analytical solutions, and providing actionable insights to stakeholders regarding feature adoption, product performance, customer satisfaction, and other critical metrics. You will also be involved in designing and delivering solutions (e.g., data sourcing, dashboards, proprietary models, visualization techniques) tailored to meet organizational needs. Clear communication of complex issues in an understandable manner is essential.

Duties & Responsibilities:

Identifying Business Objectives

• Gather and comprehend end-user requirements.

• Utilize tools such as data mapping documents, specification templates, project plans, or JIRA to effectively capture and communicate stakeholder requirements and timelines.

• Apply appropriate prioritization and scoping frameworks to manage stakeholder expectations.

Data Analysis

• Grasp the data life cycle within the digital product ecosystem, collaborating with cross-functional teams in business and technology to identify suitable data sources and definitions.

• Conduct advanced data analysis, effectively communicating and directing key insights derived from the analysis.

• Address business inquiries from multiple stakeholders and assist Product teams in making informed, data-driven decisions.

• Adhere to data security and governance protocols while managing and communicating data insights.

Building Data Analytics Pipelines

• Design ELTL workflows for repeatable, scalable, and automated solutions.

• Construct data analytics pipelines, incorporating quality checks, exploratory analysis, scheduled tasks, alerts, access control, and collaborate with enterprise analytics technology teams for production deployment.

• Innovate and implement analytical workflows and modeling approaches that leverage data assets, identifying optimal data insight tools, including advanced analytics and data science models.

Reporting and Insights

• Convert stakeholder requirements into tailored analytical solutions and communicate insights through reports, dashboards, and visualizations.

• Utilize tools such as Tableau, Power BI, and Essbase to create high-performing and scalable analytical dashboards.

• Maintain the dashboard repository and minimize redundant solutions by collaborating with cross-functional analytics teams and understanding existing reports within the organization.

• Contribute to the establishment of standards and best practices for the analytics organization. Proficiency in SAS applications, Tableau, Power BI, Microsoft Word, Excel, PowerPoint, and Visio is essential.

Qualifications
  • Basic Qualifications:
    A Bachelor's Degree and 6 years of experience in Analytics, modeling, or reporting OR a High School Diploma or GED with 10 years of experience in Analytics, modeling, or reporting.
  • Preferred Qualifications:

    • Proficiency in data analytics and visualization tools (e.g., Tableau, PowerBI, Qlik, Essbase).

    • Advanced Excel skills (e.g., pivot tables, VLOOKUP, Analysis ToolPak, macros/VBA).

    • Experience in data wrangling, workflows, and automation (e.g., SQL, Alteryx, Business Objects).

    • Familiarity with Oracle, IBM Netezza, PostgreSQL, SAS, Python, etc.

    • Expertise in analytics, reporting, data modeling, and ELTL, with proficiency in PowerPoint for creating insight presentations for various teams, including executive leadership.

    • Ability to quickly learn and adapt to different software, tools, methodologies, or coding languages.

    • Proven track record of developing custom solutions to address business challenges.

    • Experience in presenting reports, insights, and data analytics findings.

    • Relevant experience in data and analytics topics in consulting, client engagement, or project execution.

    • A willingness to learn and grow with a proactive attitude, embracing challenges and learning from failures.

    • Prior experience or domain knowledge in Digital product analytics is advantageous.

    • Knowledge of statistical or quantitative analysis (e.g., multiple regression, multivariate analysis, network analysis, AI-ML concepts and techniques).

    • Familiarity with statistical software or coding languages (e.g., Python, R, SAS).

    • Experience in data engineering with ETL tools is a significant advantage.

    • Understanding of Natural Language Processing (NLP) algorithms, tools, customer/employee survey analyses, segment analysis, and pattern detection.

    • Comfort with ambiguity and stakeholder management across various business functions.

    • Familiarity with project management concepts, including agile practices.

    • Knowledge of cloud computing approaches, such as IBM Netezza, AWS, Azure.

    • Experience or hands-on knowledge in data science, machine learning, and AI.

Preferred Area of Study: Computer Science, Statistics, Business Analytics, or related fields.
Preferred Education Level: A Master's degree is a plus.



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