Data Analyst - Sales & Technical Support

AviagenHuntsville, AL
1dOnsite

About The Position

The Sales & Technical Data Analyst transforms raw data into clear, actionable insights that strengthen customer relationships, improve internal decision-making, and elevate the effectiveness of our Sales and Technical Services teams. This role bridges the gap between complex datasets and practical business applications, delivering visual analytics and reporting that enhance both internal strategy and customer-facing presentations.

Requirements

  • Bachelor’s degree in Data Analytics, Business Analytics, Statistics, Agricultural Economics, Animal Science, Business Administration, or related field
  • 2+ years of experience in data analysis, business intelligence, or analytics roles
  • Demonstrated experience supporting commercial, technical, or customer-facing teams in data-heavy environments
  • Proven track record of translating complex data into actionable business insights
  • Advanced proficiency in Microsoft Excel (pivot tables, advanced formulas, data modeling)
  • Strong competency in at least one data visualization platform (Power BI, Tableau, or equivalent)
  • Experience creating dashboards, reports, and visual presentations for diverse audiences
  • Comfortable working with large datasets and multiple data sources
  • Exceptional communication skills with the ability to explain technical concepts in simple, accessible terms to non-technical stakeholders
  • Strong attention to detail with commitment to accuracy and data integrity
  • Excellent organizational skills and ability to manage multiple priorities simultaneously
  • Self-motivated with ability to work independently and collaboratively
  • Customer-focused mindset with understanding of how analytics support business objectives

Nice To Haves

  • Experience in agriculture, poultry, animal production, or related industries
  • Background working with Sales teams, Technical Services, or customer success functions
  • Knowledge of key performance indicator (KPI) development and commercial metrics
  • Experience with SQL, Python, R, or other data analysis programming languages
  • Familiarity with CRM systems (Salesforce, Dynamics, etc.) or ERP systems

Responsibilities

  • Design and develop clean, intuitive data visualizations from complex spreadsheets and datasets for both internal stakeholders and customer presentations
  • Build and maintain interactive dashboards, charts, templates, and recurring reports tailored to Sales, Technical Services, and leadership requirements
  • Translate performance metrics, trends, and patterns into straightforward insights for non-technical audiences
  • Standardize reporting formats to ensure consistency and professionalism across the organization
  • Prepare customer-ready analytics packages for field visits, quarterly business reviews, and technical presentations
  • Collaborate directly with Technical Managers and Sales Managers to refine data narratives, highlight value-creation opportunities, and deliver insights that resonate with customer priorities
  • Develop compelling visual presentations that position Aviagen as a strategic partner and trusted advisor
  • Ensure all customer-facing materials meet brand standards and communicate complex information clearly
  • Partner cross-functionally with Sales & Tech, Marketing, Finance, and leadership to identify data needs and close information gaps
  • Support strategic initiatives, including Joint Business Development Programs (JBDP), commercialization projects, technical programs, and market analysis
  • Facilitate data-driven decision-making by providing timely, accurate analytics for business planning and performance evaluation
  • Serve as a resource for data interpretation and analytical best practices across departments
  • Maintain clean, accurate, and well-organized data sources with consistent processes for updating and validation
  • Proactively identify data quality issues, anomalies, or improvement opportunities within production, performance, financial, and customer datasets
  • Document data sources, methodologies, and reporting processes to ensure continuity and scalability
  • Recommend improvements to data collection and management practices
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