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Guideline

Guideline is now part of @Gusto, serving 34,000+ businesses and their employees.

Senior Data Product Analyst

Product AnalystProduct AnalystOtherRemoteSeniorTeam 201-500Since 2015H1B SponsorCompany SiteLinkedIn

Location

New York

Posted

86 days ago

Salary

0

Seniority

Senior

Bachelor DegreeExperience acceptedEnglishPythonscikit-learnSQLTableau

Job Description

Senior Data Product Analyst

Guideline

• Partner with Product and Engineering teams to research, evaluate, and develop new data-driven products and feature enhancements, conducting deep analyses on complex spend, pricing, and performance datasets to identify patterns, assess data viability, and inform design decisions from concept through production. • Contribute to go-to-market release execution by validating data in production environments, coordinating QA and feature testing, preparing product collateral, and delivering internal demos to align stakeholders on new functionality — all to drive successful adoption and launch readiness. • Support release management by validating production data, investigating anomalies, providing analytical context for product and customer teams, and coordinating release communications to facilitate transparency and smooth deployment across teams. • Design and implement automated data validation and quality frameworks for digital products — defining thresholds, conditional formatting, and anomaly detection logic to proactively flag and resolve data issues, streamline QA processes, and ensure accuracy and reliability across releases. • Lead critical business-as-usual operations for monthly data releases, ensuring quality, reliability, and on-time delivery for customers by driving validation efforts, coordinating stakeholders, and resolving issues efficiently to support client retention and confidence. • Champion best practices in data governance, validation, and experimentation, establishing standards and documentation that enhance data quality, reliability, and analytical rigor across teams. • Play an active role in PI Planning, shaping backlog priorities, validating scope and acceptance criteria, and ensuring coordination across Product and Engineering teams to set realistic and value-driven delivery goals. • Leverage AI-powered analytical tools and LLM-based workflows to accelerate data validation, insight generation, and documentation. • Partner with engineering teams to integrate machine-learning–based anomaly detection and data quality checks into the product pipeline. • Identify product opportunities where AI or predictive modeling can enhance user experience, improve accuracy, or surface actionable insights. • Evaluate dataset readiness for AI/ML use cases, ensuring structures, definitions, and data governance support high-quality model performance.

Job Requirements

  • Extensive experience as a Data Analyst in a data-centric or product-driven environment, with the ability to translate analytical insights into product strategy and measurable business impact.
  • Strong analytical and problem-solving skills — able to identify trends, anomalies, and opportunities in large datasets.
  • Proficiency in SQL for querying, transforming, and validating complex datasets.
  • Hands-on experience with Power BI or equivalent BI tools (Tableau, Looker, Sisense, Qlik).
  • Demonstrated ability to communicate complex findings clearly, collaborate effectively with cross-functional teams, and influence decisions across Product, Engineering, and Operations.
  • Highly organized, detail-oriented, and proactive in managing multiple priorities and deadlines.
  • Background in media, advertising, or marketing data, with an understanding of spend, pricing, or campaign datasets.
  • Familiarity with MediaOcean (Prisma, Spectra), HudsonMX, or WideOrbit platforms.
  • Experience implementing automated QA systems, anomaly detection, or alerting frameworks for data quality.
  • Knowledge of JIRA, Confluence, and agile product development practices.
  • Strong data storytelling and business acumen, able to synthesize insights and present recommendations to senior stakeholders.
  • Familiarity with AI-assisted analytics tools (e.g., ChatGPT, Copilot, AI-based BI platforms).
  • Understanding of how data pipelines support AI models, including data labeling, data quality, and governance considerations.
  • Exposure to LLM workflows, embeddings, or vector-based search concepts (nice to have, not required).
  • Experience with Python-based data analysis or lightweight ML experimentation (scikit-learn preferred but not required).

Benefits

  • Medical
  • Dental
  • Vision
  • Health Savings Account
  • Flexible Spending Account
  • STD
  • Life
  • LTD and AD&D
  • 401(k) with a company match program
  • Unlimited Paid Time Off (PTO)
  • Paid Parental Leave
  • Commuter Benefits
  • Employee Recognition Program
  • Referral Bonus Program

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