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# Senior Data Scientist - Member Experience

- **Company:** REMOTE HAND
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $172,550.0 - $203,000.0
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Data Analysis, Cloud Computing, Information Engineering, Data Systems, Python (Programming Language), Machine Learning, Operational Data Store, Open Source Technology, SQL Databases, Large Language Models, Snowflake, Data Analytics, Data Management, Tools for Reporting, Databricks
- **Published:** August 24, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pecfop8e7g

## About the Role

Over 6 years of experience in data science, machine learning, or advanced analytics with end-to-end ownership of business problems.

Proficiency in SQL and Python, including building analytical data models and production-quality measurement systems.

Experience with NLP or LLM-based models, including open-source workflows and model quality monitoring.

Background in forecasting, time series modeling, or quantitative methods for operational planning.

Strong data engineering skills to unify and transform data for scalable analysis.

Experience with cloud and data platforms such as Databricks, AWS, dbt, or Snowflake.

Ability to communicate complex analytical concepts to non-technical stakeholders and translate outputs into actionable business recommendations.

Experience collaborating with cross-functional teams in fast-paced environments.

## Description

The Senior Data Scientist - Member Experience role is focused on advancing the support systems and analytics within the Member Experience organization. This position is responsible for developing data models and tools that enhance how members receive support throughout their journey, improving support quality, forecasting needs, and linking support interactions to broader lifecycle outcomes. The role combines technical expertise with operational insights to drive decisions that improve member satisfaction and retention.

Responsibilities

Build and maintain a quality scoring classifier for support interactions using NLP and LLM-based approaches.

Develop new support performance metrics beyond traditional volume and satisfaction measures.

Enhance forecasting models for support volume, capacity, and staffing demand.

Link support interactions to member identities and lifecycle data to analyze support quality and retention outcomes.

Collaborate with Member Experience, operations, and cross-functional teams to define problems and implement data solutions.

Create dashboards and reporting tools to provide visibility into support quality and member outcomes.

Utilize SQL, Python, and data engineering skills to transform operational data into actionable insights and production-ready systems.


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