Sr Product Analyst

Job Title: Senior Product Analyst - Real World Data

Job Description:

We are seeking a highly skilled and experienced Senior Product Analyst to join our Real World Data team.

Your primary responsibility will be to become an expert in our multimodal data and to deliver insights and analyses on this data to our customers. You’ll support end-to-end analytical product development in Amazon QuickSight, Snowflake, and Plotly Dash—translating stakeholder needs into the first versions of customer-facing software. You will also help define the semantic layer (metrics and definitions), establish analytics workflows and quality standards, and mentor other analysts through review and best practices.

Responsibilities:.

• Data Analysis: Use SQL (and Python/R) to extract insights, generate reports and conduct deep-dive analysis from multimodal data. 

• Analytical Tool Development & Visualization: Maintain and build analytical tools and customer-facing dashboards (QuickSight) plus internal apps/prototypes (Plotly Dash/Streamlit strongly preferred) to accelerate exploration and stakeholder decision-making.

• Cross-functional Partnership: Collaborate with stakeholders, domain experts, Product, and Data Engineering to understand needs, align on definitions, and deliver analytical products.

• Analytical Process: Define best practices, processes, and methodologies (intake/prioritization, QA, documentation, release notes). Create standards for the analytics team code style, improve code/dashboard performance, and own documentation of data and logic.

• Intermediate Data Modeling & Semantic Layer: Design and document intermediate analytical models that power dashboards and self-serve analysis. Own metric definitions, calculation standards, and a shared “source of truth” for business logic.

Required Qualifications:

• Bachelor's or Master's degree in Computer Science, Data Science, Business Analytics, Mathematics, Healthcare, or a related field.

• Proven experience (5+ years) as a Product Analyst, Data Analyst, Business Analyst or similar role, with a strong focus on analytics and development of visualization tools.

• Proficiency with data analysis tools including SQL and Excel and data warehouses such as Redshift, BigQuery or Snowflake.

• Experience with analytical data modeling and/or semantic layers (metric definitions, dimensional models, governed datasets).

• Experience with Python or R.

• Demonstrated experience shipping customer-facing dashboards (QuickSight or similar), including requirements gathering and iteration based on user feedback.

• Strong communication and presentation skills, with the ability to convey complex analytical findings to technical and non-technical stakeholders.

Preferred Qualifications:

• Experience building analytical apps using Plotly Dash, Streamlit or equivalent

• Knowledge of statistical analysis, predictive modeling and machine learning techniques.

• Understanding of ETL technologies, Connector Management, Data Management & Analytics platforms.

• Prior experience working with complex healthcare data modalities, such as claims data, electronic health records (EHR), omics data (e.g., genomics, proteomics), and other healthcare-related datasets.

• Prior work evaluating or enabling AI/LLM analytics interfaces with emphasis on semantic correctness, guardrails, and trustworthy outputs. 

The pay range is listed and actual compensation packages are based on a wide array of factors unique to each candidate, including but not limited to skill set, years & depth of experience, certifications and specific office location. This may differ in other locations due to cost of labor considerations.Remote USA$117,600—$147,000 USD

OUR OPPORTUNITY

Natera™ is a global leader in cell-free DNA (cfDNA) testing, dedicated to oncology, women’s health, and organ health. Our aim is to make personalized genetic testing and diagnostics part of the standard of care to protect health and enable earlier and more targeted interventions that lead to longer, healthier lives.

The Natera team consists of highly dedicated statisticians, geneticists, doctors, laboratory scientists,