Senior CX Insights Analyst

Gainwell Technologies LLC

1d•Remote

About The Position

The Sr. Professional Data Analyst delivers scalable, omnichannel insights by combining advanced analytics, data engineering, and storytelling. This role partners cross‑functionally to define key metrics, build and maintain data pipelines and dashboards, and analyze large structured and unstructured datasets to surface trends, risks, and improvement opportunities across customer and operational journeys. The analyst stitches data across channels to create a holistic view, applies advanced techniques (including text analysis where applicable), and translates complex findings into clear, actionable recommendations for executives and operational teams. The role emphasizes data quality, governance, continuous improvement, and efficiency through automation and process optimization, particularly within healthcare, insurance, and claims environments.

Requirements

2–5 years of experience in Data Analytics.
Experience in Python and/or other data scripting languages and hands-on experience with a BI visualization tool (Power BI, Tableau, Cognos, etc.).
Strong SQL querying and data modeling skills, with experience analyzing large structured and unstructured datasets (e.g., text, transcripts, logs).
Ability to stitch structured and unstructured data to produce omnichannel insights and detect emerging trends or pain points.
Experience with cloud data environments (AWS or Azure preferred).
Experience with data governance, data quality concepts, or data quality tools.

Responsibilities

Collaborate with team members and stakeholders to define key business metrics, deeply understand business challenges, and gather requirements for insights that should be made available at scale.
Architect and maintain data pipelines, design data models, and build new dashboards to address stakeholder needs across multiple business domains.
Analyze large volumes of structured and unstructured data (text, logs, call notes, chat transcripts, surveys, etc.) to surface emerging trends, signals, and potential pain points in customer and operational journeys.
Stitch structured and unstructured datasets to deliver holistic, omnichannel insights, providing a full customer and operational view across channels.
Apply NLP, classification techniques, clustering, or pattern‑detection methodologies (where applicable) to discover insights—following the data to uncover hidden opportunities or emerging issues.
Deliver clear, compelling presentations that translate complex analytical findings into actionable recommendations for executives and operational teams.
Maintain and enhance existing data infrastructure, dashboards, and reporting assets based on evolving business needs.
Publish and maintain clear documentation to inform and educate users at scale, gather feedback, and identify opportunities for improvement.
Identify ways to streamline and improve efficiency across channels, including workflow automation and process optimization.
Work cross‑functionally with product, engineering, operations, CX, data governance, and other teams to align on data needs, requirements, and solutions.
Stay organized, manage multiple priorities, and adjust analytical approaches as new data signals or unexpected patterns emerge.