Senior Data Product Analyst

Join YipitData, a leading provider of alternative data, as a Senior Data Product Analyst. In this pivotal role, you will be at the forefront of our AI-powered product initiative, transforming how clients interact with data. You will own the path from raw alternative data to trusted, product-ready intelligence, and work closely with diverse datasets to develop methodologies that turn signals into reliable business insights. Your work will directly influence how hundreds of customers interact with our data and how this product scales over time.

• Posséder la responsabilité de la traduction de jeux de données alternatifs bruts en produits de données évolutifs et prêts pour l'IA.
• Concevoir des méthodologies qui répondent à des questions commerciales de grande valeur, en déterminant comment les ensembles de données disparates doivent être combinés, normalisés et interprétés.
• Collaborer étroitement avec l'ingénierie des données pour façonner les pipelines de données sources en ensembles de données propres et bien structurés.
• A demonstrable track record of building—shipping things, solving hard problems, and leaving a clear mark on the products you’ve worked on
• 3–6 years of experience in data product management, product analytics, analytics engineering, data science, market intelligence, alternative data, or a closely related field
• Prior experience in or exposure to AI/ML products, LLM-based agents, or evaluation frameworks is a strong plus
• Strong project management instincts: you can run a triage process, maintain a quality library, and coordinate across multiple stakeholder groups without dropping balls
• Strong fluency in SQL; comfort with data pipelines, schema changes, and upstream/downstream data dependencies
• A track record of cross-functional coordination, ideally between technical data teams and product or commercial stakeholders
• Experience owning data documentation, metric definitions, or data quality programs—not just conducting ad hoc analysis
• Deep experience with alternative data, panel data, or similarly complex, nuanced data sources is required—you need to understand the quirks, limitations, and methodological subtleties of these datasets and be able to encode that understanding for an AI driven product
• Clear, structured communication—you can translate complex data methodology questions into guidance that non-technical stakeholders can act on
• An entrepreneurial mindset: you’re comfortable with ambiguity, energized by new problem spaces, and don’t need a fully paved road to make progress