Senior Product Analyst

Passionate about food? Eager to join a dynamic SaaS startup shaping the food and beverage industry? Tastewise is just the place for you.

Tastewise: The GenAI-powered consumer data platform revolutionizing product strategies and driving success for major brands like Nestle, Pepsi, and Campbell’s. With insights from billions of data points, we empower our clients to create, market, and sell their products faster and more successfully.

Join this $10 trillion industry, where creativity and an entrepreneurial mindset drive daily success and reach the homes of billions of people in an industry where change isn't just a recipe but a way of life.

Let's shape the future of food together.

About the role:

The Product Analyst will analyze complex data sets, support product teams in defining KPIs, and generate actionable insights to improve business outcomes. The ideal candidate will be a proactive problem-solver who can collaborate effectively across teams to enhance user satisfaction and drive business performance.

Responsibilities:

Product Lifecycle and development: Actively engage in all phases of the product lifecycle, including:

• Generating ideas for new products and features.
• Helping design solutions that address customer needs.
• Collaborating with R&D to ensure requirements are delivered accurately.
• Validating that the product provides actionable insights to customers.
  
  

• Define KPIs for products and features.
• Track results and measure the business impact of product launches.
• Provide actionable insights to improve product performance and customer satisfaction.
  
  

• Minimum of 4 years in a product analytics or similar role at a product-focused company, ideally within a B2B SaaS environment.
• Demonstrated ability to align analytics with business objectives and outcomes.
• Previous experience working on a data or BI product is a significant advantage.
• Excel: Advanced proficiency, capable of creating complex models and analyses.
• SQL: Advanced expertise for querying, analyzing, and managing large datasets.
  
  

• Python (pandas and visualization libraries such as Matplotlib, Seaborn, or Plotly).
• User analytics tools (Mixpanel, Amplitude)
• Elasticsearch for handling and querying large volumes of data.
• Salesforce for sales and customer data analysis.
• Familiarity with GenAI models and experience in AI applications (Like RAG)