Enterprise Transfer Intelligence Data Scientist - Remote

UnitedHealth Group•Minnetonka, MN

2d•$72,800 - $130,000•Remote

About The Position

The Enterprise Transfer Intelligence Data Scientist advances UnitedHealthcare’s Contact Center Transformation Transfer Reduction initiative by developing and operationalizing enterprise Transfer Intelligence capabilities. The role uses AI, machine learning, advanced analytics, statistical modeling, and large language models to identify, explain, predict, and reduce unnecessary transfers across the enterprise. Working with call transcripts, routing and authentication data, telephony platforms, operational metrics, and customer interaction data, the Data Scientist turns complex information into actionable intelligence. The work supports improved routing effectiveness, fewer avoidable handoffs, increased first-contact resolution, optimized contact center operations, and a better customer experience. The position converts transfer intelligence into measurable business outcomes through analytics, opportunity identification, decision-support products, and ongoing optimization across multiple lines of business. The position is remote within the U.S. Employees hired in the Minneapolis or Washington, D.C. area must work in the office at least four days per week. Remote employees must follow UnitedHealth Group’s Telecommuter Policy.

Requirements

Intermediate to advanced experience using SQL and Python to analyze large, complex datasets.
Intermediate to advanced experience applying statistical analysis, machine learning, predictive modeling, or artificial intelligence to solve business problems.
Proven experience translating business challenges into analytical solutions and actionable recommendations.
Proven experience working with structured and unstructured datasets.
Proven communication skills, including the ability to explain complex analytical concepts to business stakeholders.

Nice To Haves

Experience using Databricks, Azure, Snowflake, Power BI, or related analytics platforms.
Experience with large language models, generative AI, prompt engineering, or NLP-based solutions.
Experience working with call transcripts, speech analytics, conversational AI, or customer interaction data.
Experience in contact center analytics, customer experience analytics, healthcare operations, or workforce optimization.
Experience designing and operationalizing analytical products used by business stakeholders.
Experience supporting enterprise transformation initiatives through advanced analytics.

Responsibilities

Analyze transfer behavior across multiple lines of business and identify opportunities to reduce avoidable transfers.
Conduct destination analysis to identify transfer hotspots, recurring patterns, ineffective handoffs, and routing breakdowns.
Identify and quantify drivers of multi-transfer, ping-pong, repeat-transfer, and incorrect-destination interactions.
Evaluate relationships between transfers and authentication outcomes, routing design, agent skill alignment, business processes, technology limitations, and customer needs.
Develop forecasting and scenario-modeling techniques to estimate the impact of transfer-reduction initiatives.
Deliver prioritized recommendations that influence routing strategies, staffing decisions, training investments, operational processes, and technology improvements.
Develop, maintain, and enhance analytical models supporting enterprise transfer reduction.
Operationalize and continuously improve transfer root-cause analytics capabilities.
Apply machine learning, natural language processing, large language models, and statistical techniques to structured and unstructured data.
Monitor model performance, identify drift, evaluate accuracy, and recommend enhancements.
Integrate additional data sources, including call transcripts, routing activity, authentication outcomes, IVR interactions, queue behavior, and operational metrics.
Refine classification taxonomies, prompts, business rules, and analytical frameworks to improve insight quality and business value.
Research emerging AI capabilities and evaluate how they can improve transfer analytics and opportunity identification.
Design, develop, and enhance enterprise Transfer Intelligence products and analytical solutions.
Support the evolution of Transfer Genie, Databricks-based products, semantic layers, and AI-enabled self-service experiences.
Develop reusable analytical assets, governed metrics, and scalable data products for enterprise-wide transfer analysis.
Partner with stakeholders to prioritize product enhancements and identify new analytical capabilities.
Translate complex analytical findings into actionable business insights for technical and non-technical audiences.
Lead investigations into transfer-rate changes, migration impacts, routing concerns, authentication trends, and operational performance issues.
Analyze how telephony, platform, and operational changes affect transfer behavior.
Validate transfer classifications, business rules, and reporting logic for consistency and accuracy across reporting products.
Identify root causes of unexpected transfer trends and recommend remediation strategies.
Partner with operations, product, and technology teams to assess implemented solutions and identify further optimization opportunities.
Measure and quantify the effectiveness of transfer-reduction initiatives.
Establish methodologies to track business value and operational impact from transfer intelligence recommendations.
Assess routing enhancements, authentication improvements, AI-enabled capabilities, technology investments, and process changes.
Develop executive-ready narratives, presentations, and recommendations connecting analytical findings to business outcomes.
Provide ongoing analytical support and recommendations to CCT leadership and Transfer Workstream stakeholders.