Job Summary

We are seeking a highly curious, execution-focused Senior Data Scientist to play a critical role in advancing the Call Center Innovation Lab (CCIL). This contract-to-hire, remote role is focused on applying AI, advanced analytics, and Contact Intelligence to improve digital self-serviceability, customer experience, and call center efficiency at scale. The role will work extensively with call transcripts and large volumes of document and text-based data, using Large Language Models (LLMs), transformer models, and Natural Language Processing (NLP) techniques to extract actionable insights. The successful candidate will be responsible for model development, training, data collection, stakeholder interaction, and iterative delivery from raw data through finished analytical products. The role will also support expansion of existing solutions across additional lines of business and product areas, including development of new models to extract additional insights.

Key Responsibilities

• Lead end-to-end analytical and modeling execution for Call Center Innovation Lab initiatives, including opportunity identification, metric definition, framework design, analysis, model development, training, and insight generation.

• Analyze large volumes of call center interaction data, including call topics, transcripts, summaries, chat logs, and other unstructured text, to identify member service drivers, efficiency gaps, and digital self-service opportunities.

• Build, train, evaluate, and fine-tune models using LLMs, transformer models, NLP techniques, and other appropriate data science approaches.

• Develop information-extraction models to identify insights from raw text-based data, such as whether an issue was resolved, what a customer was asking about, and the types of benefits, medications, or services discussed.

• Expand existing AI and NLP solutions across additional lines of business and product areas.

• Develop new models and analytical capabilities to extract additional types of insights from contact center data.

• Collect, prepare, and analyze data required for model development and training.

• Apply emerging LLM, transformer, NLP, and GenAI techniques to unstructured and conversational data.

• Develop and operationalize standardized analytical and digital self-serviceability frameworks that are scalable, maintainable, and adaptable as digital capabilities evolve.

• Partner closely with Digital SMEs and Call Center Operations stakeholders to assess which member needs and call drivers can be addressed through existing or planned digital capabilities.

• Design and evaluate pilots, experiments, or quasi-experiments to quantify impact and inform data-driven decisions.

• Translate complex analytical and modeling findings into clear, actionable insights and narratives for technical and senior business stakeholders.

• Explain model capabilities, outputs, limitations, and technical tradeoffs in clear, non-technical language.

• Demonstrate the business value, ROI, and impact of analytical and AI solutions to stakeholders.

• Support the transition of analytical outputs into dashboards, scorecards, or reusable data assets in collaboration with data engineering and platform partners.

• Work independently with limited ramp-up time and take ownership of the full analytical and modeling lifecycle from raw data through finished product.

• Collaborate with separate data engineering and production engineering teams responsible for data engineering and productionizing models.

Required Qualifications

• 3+ years of experience in data science or advanced analytics, with demonstrated experience delivering end-to-end analytical or modeling solutions.

• Strong hands-on experience with SQL and Python for data analysis and modeling.

• Hands-on experience applying Large Language Models (LLMs), Natural Language Processing (NLP), Generative AI (GenAI), or transformer models to text or conversational data.

• Strong experience working with text-based, unstructured, or document data.

• Experience with model development, training, evaluation, and fine-tuning.

• Experience designing and evaluating experiments, pilots, quasi-experiments, or A/B tests and translating results into business recommendations.

• Experience building analytical assets intended for ongoing use, including frameworks, scorecards, dashboards, or reusable models, with an emphasis on iteration and refinement.

• Strong communication skills, with the ability to clearly explain insights, model capabilities, tradeoffs, and recommendations to both technical and non-technical audiences.

• Demonstrated ability to work cross-functionally and navigate ambiguity in fast-moving environments.

• Strong stakeholder management skills and the ability to understand and synthesize stakeholder requirements.

• Demonstrated ability to independently drive analytical and modeling initiatives with limited ramp-up time.

• Experience with version control, such as Git, and familiarity with modern data workflows or orchestration tools.

Preferred Qualifications

• Experience working with call center, virtual assistant, or contact center data, including voice, transcripts, chat, IVR, routing, or agent interactions.

• Familiarity with Vertex AI and Google Cloud Platform (GCP), or equivalent enterprise AI platforms such as AWS or Azure.

• Experience using Gemini foundation models or comparable foundation models.

• Experience analyzing digital, customer interaction, or call center data.

• Experience communicating technical tradeoffs and business impact to senior stakeholders.

• Experience in healthcare, insurance, or related customer-service environments.

• Master’s degree in Computer Science, Engineering, Analytics, Statistics, or a related quantitative field.

Education

• Bachelor’s degree in Computer Science, Engineering, Analytics, Statistics, or a related quantitative field.

• Master’s degree preferred.