1

Product Analytics Jobs in Georgia (NOW HIRING)

Sr Data Analyst, Product

Atlanta, GA · On-site

$110 - $140/hr

Cross-Team Analytics Support * Build and maintain dashboards and self-serve reporting that let Product Managers track their product area's P&L, feature usage, and client adoption without a one-off ...

New

$71K - $95K/yr

Own the measurement of our data products end to end: usage and consumption analytics, activation and success metrics, and their connection to downstream revenue, upgrades, expansion, and retention.

Showing results 41-60

Product Analytics information

See Georgia salary details

$43.5K

$134.6K

$166.3K

How much do product analytics jobs pay per year?

As of Sep 3, 2026, the average yearly pay for product analytics in Georgia is $134,599.00, according to ZipRecruiter salary data. Most workers in this role earn between $119,100.00 and $166,300.00 per year, depending on experience, location, and employer.

What is product analytics?

A Product Analytics job involves using data to evaluate and optimize a company's products. Analysts in this role collect, analyze, and interpret user behavior data to provide insights that drive product decisions. They work closely with product managers, engineers, and designers to improve user experience and business outcomes. Key responsibilities include tracking key metrics, running experiments (A/B testing), and generating reports to support data-driven decision-making.

What does a typical day look like for someone in product analytics?

A typical day in Product Analytics involves analyzing user behavior data, building dashboards, and creating reports to help teams make product decisions. You will work closely with product managers, designers, and engineers to identify key performance indicators (KPIs), design and assess A/B tests, and provide insights for new feature development. Regular meetings and collaboration with cross-functional teams are common, as is presenting findings and recommendations to stakeholders. This dynamic environment offers the opportunity to influence product strategy and prioritize improvements based on data-driven evidence.

What are the key skills and qualifications needed to thrive in product analytics, and why are they important?

To thrive in Product Analytics, you need a strong background in data analysis, statistical modeling, and a good understanding of product lifecycle concepts, often supported by a degree in statistics, computer science, or a related field. Familiarity with tools such as SQL, Tableau, Python or R, and analytics platforms like Google Analytics or Mixpanel is critical, and some roles may prefer certification in analytics or data science. Strong communication, business acumen, and problem-solving skills help you translate complex data into actionable insights for cross-functional teams. These capabilities are essential for driving product enhancements, optimizing user experience, and supporting business growth through informed decision-making.

What are the most commonly searched types of Product Analytics jobs in Georgia?

The most popular types of Product Analytics jobs in Georgia are:

What are popular job titles related to Product Analytics jobs in Georgia?

For Product Analytics jobs in Georgia, the most frequently searched job titles are:

Infographic showing various Product Analytics job openings in Georgia as of August 2026, with employment types broken down into 81% Full Time, 16% Part Time, 2% Contract, and 1% Nights. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $134,599 per year, or $64.7 per hour.

Sr Data Analyst, Product

Socket.dev

Atlanta, GA • On-site

$110 - $140/hr

Other

Posted 2 days ago

New


Key responsibilities

  • Analyze insurance eligibility and coverage data to track active coverage rate, plan identification accuracy, and eligibility flag clearance.

  • Build and maintain recurring client-facing and internal outcome reporting, consolidating data from internal sources into reusable data models.

  • Build and maintain dashboards and self-serve reporting to track product area's P&L, feature usage, and client adoption.


Job description

About the Role

The Senior Data Analyst, Product will be the analytical backbone for active product initiatives around Eligibility, AI, Revenue Analysis, and Client Outcomes. You will also support the broader Product team's move toward outcome-based measurement across Scheduling, Registration, Intake, and Payments.

Clearwave's Product Management team operates under a Product Operating Model, which means every product manager is expected to lead with continuous discovery, define success metrics before building, and report on business outcomes rather than just features shipped. This Data Analyst role supports turning scattered exports, portal reports, and Salesforce data into the metrics, dashboards, and analysis our business needs to prove value and make evidence-based prioritization calls.

Key Responsibilities

Eligibility AI

  • Analyze insurance eligibility and coverage data across the scheduling, pre-registration, and visit stages of the patient journey to track active coverage rate, plan identification accuracy, and eligibility flag clearance.
  • Monitor accuracy and performance of AI-driven eligibility checks (e.g., Code 42 non-response, flag resolution), and surface trends by payer, location, and client.
  • Partner with the Eligibility AI product manager to define and track success metrics before development begins, and report on outcomes (clean-claim impact, staff time saved, denial reduction) after launch.

Revenue Analysis

  • Support revenue and opportunity modeling for initiatives, including attach-rate assumptions, unit economics, and renewal risk analysis.
  • Pull and validate Salesforce data (strategic renewals, new-logo run-rate) feeding the opportunity model, flagging data-mapping issues before they reach leadership reporting.
  • Help quantify and track initiative adoption and revenue contribution against goals set by the product and revenue teams.

Client Outcomes Data

  • Build and maintain recurring client-facing and internal outcome reporting (usage, adoption, satisfaction, business impact) across product areas, in the spirit of the outcome-measurement goals every PM on this team is held to.
  • Consolidate exports from the Clearwave Provider Portal and other internal sources into consistent, reusable data models so reporting doesn't have to be rebuilt from scratch each cycle.
  • Help Product Managers document ROI for completed initiatives (e.g., Payment at Pre-Reg, Voice AI, Reschedule Assist) using adoption rates, transaction/revenue volume, and customer satisfaction data.

Cross-Team Analytics Support

  • Build and maintain dashboards and self-serve reporting that let Product Managers track their product area's P&L, feature usage, and client adoption without a one-off analysis request each time.
  • Translate ambiguous business questions from Product, CS, and leadership into clean data pulls, clear visualizations, and a defensible recommendation.
  • Maintain data quality and documentation for the metrics and definitions this team relies on, so numbers stay consistent across PMs and reporting cycles.
  • Participate in discovery and prioritization conversations to make sure decisions are grounded in usage and outcome data, not just anecdote.
What Success Looks Like in the First Year
  • Eligibility AI, Revenue Analysis, and Client Outcomes each have a standing set of metrics, defined with their product owners, that are tracked and reported on a regular cadence rather than assembled ad hoc.
  • Product Managers can pull adoption, usage, and revenue-impact data for their product area without waiting on a custom analysis.
  • Initiatives have documented before/after outcome story (e.g., ROI, time saved, adoption growth) built from your reporting.
Technical Environment

This role works hands-on across our modern data stack and product platform. Familiarity with the following technologies, or the ability to ramp quickly, is central to success in this position.

Data & Analytics
  • Snowflake (medallion architecture) – enterprise data platform and system of record for analytics.
  • AWS Glue and Kafka – data ingestion and pipeline infrastructure feeding the warehouse.
  • Legacy SQL Server EDW (15TB+)
  • Tableau
  • Power BI
Required Qualifications
  • 5+ years of experience in a data analyst, business analyst, or product analyst role, ideally supporting a product or SaaS organization.
  • 5+ years of experience and expertise in data structures, indexing, querying, and data retrieval concepts
  • Experience in Big Data tools and languages (golang, python, spark)
  • Strong SQL skills and comfort working directly with relational databases or a data warehouse.
  • Experience building dashboards and reports in a BI/visualization tool (e.g., Power BI, Tableau, Looker) or in spreadsheet-based tooling at scale.
  • Ability to turn a loosely defined business question into a structured analysis and communicate the findings clearly to non-technical stakeholders.
  • Comfort working with CRM data; Salesforce reporting experience preferred.
  • Bachelor's degree in a quantitative, business, or related field, or equivalent professional experience.
Preferred Qualifications
  • Experience in healthcare, health-tech, or another regulated data environment, with an understanding of handling sensitive data appropriately (HIPAA awareness).
  • Familiarity with Python or R for data cleaning and analysis at scale.
  • Exposure to product analytics concepts (adoption funnels, cohort analysis, activation/retention metrics) and to empowered product-team operating models.
  • Experience working with EHR, PM system, or patient-scheduling data.
  • Exposure to streaming and batch data pipeline tooling (Kafka, AWS Glue or similar) and to large-scale transactional datasets (millions of records per day).
  • Familiarity with AI/ML-driven analytics – evaluating model or rules-engine output (e.g., Drools), monitoring accuracy and drift, and translating AI performance into business metrics.
  • Experience supporting a platform migration (e.g., SQL Server to Snowflake, Power BI to Tableau) while maintaining reporting continuity.
#J-18808-Ljbffr