Senior Data Analyst (Full-Time Contractor)

Overview:

Nerdy is looking for a talented Senior Data Analyst (full-time contractor) based in South America to help with our ongoing growth and expansion! The Senior Data Analyst role at Nerdy is a hybrid role that combines the responsibilities of an Analytics Engineer and a Data Analyst. It requires the technical expertise to own and maintain the data transformation layer and to enable data self-service through advanced Looker development. It also demands a strong analytical mindset to define key metrics, build impactful reports, surface trends/insights, and collaborate closely with senior business leaders. The ideal candidate will bring a rare combination of technical rigor and business fluency that allows them to bridge the gap between data infrastructure and strategic decision-making.

About Nerdy:

Nerdy (NYSE: NRDY), the parent company of Varsity Tutors, is a leading platform for live online learning, with a mission to transform the way people learn through technology. The Company’s purpose-built proprietary platform leverages technology, including AI, to connect learners of all ages to experts, delivering superior value on both sides of the network. Nerdy’s comprehensive learning destination provides learning experiences across 3,000+ subjects and multiple formats—including one-on-one instruction, small group classes, large format group classes, and adaptive self-study. Nerdy’s flagship business, Varsity Tutors, is one of the nation’s largest platforms for live online tutoring and classes. Its solutions are available directly to students and consumers, as well as through schools and other institutions.  Nerdy is a publicly traded company on the New York Stock Exchange. Learn more about Nerdy at https://www.nerdy.com/.

Nerdy’s shareholder letters below explain the product and strategy and are the most effective way to learn about what the company is building. 

• Q1-2025 Shareholder Letter
• Q4-2024 Shareholder Letter
• Q3-2024 Shareholder Letter

Qualifications:

• Bachelor's degree in a technical or quantitative field (e.g., Computer Science, Information Technology, Statistics, Mathematics, or related)
• Minimum of 5 years of experience in data analytics, business intelligence, or analytics engineering roles
• Strong proficiency in SQL and additional programming experience (e.g., Python, R, SAS, SPSS)
• Extensive experience with BI visualization tools (e.g., Looker, Tableau, Power BI, Qlik).  Specific experience with Looker development is a big plus.  
• Strong attention to detail and commitment to data accuracy and integrity
• Demonstrated ability to define and operationalize core business metrics in partnership with stakeholders
• Excellent analytical and problem-solving skills with the ability to interpret complex data, identify trends, generate insights, and support data-driven decision-marking
• Strong communication and collaboration skills; ability to translate technical findings into business-friendly narratives and partner effectively with senior leaders.
• Comfortable working in fast-paced, cross-functional environments, managing multiple priorities while maintaining attention to detail.

Responsibilities:

• Own and evolve the data transformation layer, including building and maintaining robust, scalable models in tools like Looker, DBT, or equivalent SQL-based frameworks.
• Design and develop the Looker semantic layer (LookML), including views, explores, dashboards, and governed metrics that power self-service analytics across the organization.
• Define, document, and maintain key business metrics in collaboration with stakeholders to ensure consistency and clarity in reporting and decision-making.
• Build and deliver insightful, high-impact analyses that identify trends, uncover opportunities, and inform strategic initiatives.
• Leverage AI and machine learning tools to accelerate analysis, automate workflows, and generate deeper insights from large and complex datasets.
• Partner closely with senior business leaders to understand their goals, translate questions into analytical problems, and communicate findings effectively.
• Promote self-service analytics by developing intuitive Looker experiences and training end users to explore and interpret data independentl