Senior Data Analyst

At ALLO, we believe people are our biggest asset. Our team brings the ALLO mission to life because as local members of each community, we live, work, play, and volunteer right here with you. We're passionate about being involved and contributing to the success and progress of each of our GIG Communities.

We pursue these passions because ALLO leaders have created a workplace where folks are valued, ideas are heard, and leaders and teammates show up for each other at work and in life.

The Senior Data Analyst is a highly analytical and business-savvy individual contributor who acts as an internal expert and strategic partner to various business units. This role focuses on tackling complex business challenges by leveraging data for decision-making and delivering actionable analytical solutions. The Senior Data Analyst works closely with stakeholders to address assigned projects, guiding them through a data-driven process and often leading the technical execution of analytical work by collaborating with data engineers, data scientists, and other data analysts. A key part of this role is not only delivering insights but also proactively identifying and implementing process improvements to enhance efficiency and effectiveness. This is a critical role for driving data literacy and adoption throughout the company.

RESPONSIBILITIES:

• Business Problem Framing & Solution Definition:  

  • Proactively engage with business stakeholders (e.g., Marketing, Sales, Product, Operations, Finance) to understand their objectives, challenges, and data needs for assigned projects. 

  • Translate vague business questions into clear, measurable analytical problems and hypotheses. 

  • Scope and define analytical projects, outlining objectives, deliverables, timelines, and required resources. 

  • Recommend the most appropriate analytical approaches and methodologies (e.g., descriptive, diagnostic, predictive, prescriptive analytics). 

• Data Analysis & Insight Generation:  

  • Conduct in-depth data analysis using various tools and techniques to uncover trends, patterns, and insights. 

  • Develop compelling narratives around data findings and present insights in a clear, concise, and actionable manner to diverse audiences. 

  • Utilize advanced analytical techniques (e.g., statistical analysis, A/B testing design, segmentation) to answer critical business questions. 

• Stakeholder Engagement & Relationship Management:  

  • Build strong, trusted relationships with business leaders and team members across the organization. 

  • Facilitate workshops and discussions to gather requirements and validate analytical outputs. 

  • Champion data-driven decision-making and enhance data literacy within business units. 

  • Manage expectations and communicate progress, challenges, and outcomes effectively. 

• Tooling & Best Practices:  

  • Stay abreast of industry trends, new analytical tools, and methodologies. 

  • Advise on the selection and effective use of analytics and AI tools (e.g., BI platforms, statistical software, latest models and features). 

  • Contribute to the continuous improvement of analytical processes and best practices within the Data & Analytics department.

EDUCATION/EXPERIENCE:

• Bachelor's degree in Statistics, Mathematics, Data Science, Computer Science or a related quantitative field. Master's degree preferred. 

• 3+ years of experience in an analytical role, such as a Senior or Lead Data Analyst, Senior or Lead Business Analyst, or Data Scientist with a strong focus on stakeholder engagement and solution delivery. 

SKILLS / KNOWLEDGE / ABILITIES:

• Proven ability to translate complex business problems into analytical requirements and deliver actionable insights. 

• Strong proficiency in SQL for data extraction, manipulation, and analysis. 

• Experience with scripting languages for data analysis (e.g., Python, R). 

• Experience with data visualization and dashboarding in Looker.

• Familiarity with AI agents and their role in delivering data analysis to non-technical stakeholders.

• Demonstrated experience with statistical analysis and data interpretation. 

• Excellent communication, presentation, and storytelling skills, with the ability to articulate complex data insights to non-technical audiences. 

• Strong project management skills, with the ability to manage multiple priorities and deadlines.