We are seeking a Modeler to contribute to the development of AI/ML solutions that improve contact center efficiency and member experience. You will build and optimize models supporting call deflection, intelligent routing, agent assist, and quality monitoring initiatives. Working in a collaborative team environment, you will apply machine learning and NLP techniques to operational data and support the full model development lifecycle.
Responsibilities- Develop and optimize machine learning models for call deflection prediction, intelligent routing, and automated quality monitoring.
- Apply NLP techniques to analyze call transcripts and digital interaction logs to classify intent, detect topics, and surface automation opportunities.
- Perform feature engineering on structured and unstructured operational data sources including CRM records, call logs, and interaction metadata.
- Support end-to-end model lifecycle activities including data preparation, model training, evaluation, documentation, and performance monitoring.
- Design and execute A/B tests or champion-challenger evaluations to measure model impact on operational KPIs.
- Collaborate with contact center operations and technology teams to understand workflows and integrate model outputs into existing systems.
- Prepare clear model documentation covering methodology, assumptions, performance metrics, and monitoring plans.
- Monitor deployed models for drift and degradation, escalating issues and recommending retraining or recalibration as needed.
- Stay current on advances in conversational AI, NLP, and operational analytics.
- 3–6 years of experience in data science, analytics, or machine learning with exposure to operational or contact center domains.
- Working knowledge of NLP techniques including text classification, entity extraction, and sentiment analysis.
- Proficiency in Python; familiarity with libraries such as scikit-learn, spaCy, Hugging Face, pandas, and numpy.
- Experience with SQL and working with large, complex operational datasets.
- Understanding of contact center metrics such as handle time, first-call resolution, CSAT, and deflection rates is preferred.
- Familiarity with model validation concepts, performance evaluation frameworks, and documentation standards.
- Strong analytical and problem-solving skills with a practical, solutions-oriented mindset.
- Effective communication skills for presenting analytical findings to both technical peers and operational stakeholders.
- Bachelor's degree (Master's preferred) in Computer Science, Statistics, Engineering, or a related quantitative discipline.
Skills Required
- 3-6 years of experience in data science, analytics, or machine learning
- Experience with operational or contact center domains
- Working knowledge of NLP techniques, including text classification, entity extraction, and sentiment analysis
- Proficiency in Python
- Experience with SQL and large, complex operational datasets
- Familiarity with scikit-learn, spaCy, Hugging Face, pandas, and NumPy
- Familiarity with model validation, performance evaluation frameworks, and documentation standards
- Strong analytical and problem-solving skills
- Effective communication skills for technical and operational stakeholders
- Bachelor's degree in Computer Science, Statistics, Engineering, or a related quantitative discipline
- Master's degree
- Understanding of contact center metrics such as handle time, first-call resolution, CSAT, and deflection rates
EXL Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about EXL and has not been reviewed or approved by EXL.
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Healthcare Strength — Medical plan options include HSA, HRA, and PPO choices, with additional health-related programs such as disability coverage and an employee assistance program. Feedback suggests these options provide meaningful flexibility and coverage breadth for many roles.
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Leave & Time Off Breadth — Up to 20 days of paid time off, plus federal holidays and paid sick and safe time, are highlighted. Feedback suggests this leave structure is a notable benefit alongside core compensation.
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Retirement Support — A traditional and Roth 401(k) with up to a 3% company match and full vesting after one year is described. Feedback suggests this match and vesting timeline help bolster long-term savings.
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Choosing a digital partner is about more than capabilities — it’s about collaboration and character. Unrealistic overhauls and off-the-shelf products ignore what matters most — your unique needs, culture, goals, and your legacy data and technology environments. At EXL, our collaboration is built on ongoing listening and learning to adapt our methodologies. We’re your business evolution partner—tailoring solutions that make the most of data to make better business decisions and drive more intelligence into your increasingly digital operations. Whether your goals are scaling the use of AI and digital, redesign operating models, or driving better and faster decisions, we’re here to partner with you to help you gain—and maintain—competitive advantage with efficient, sustainable models at scale. Our expertise in transformation, data science, and change management helps make your business more efficient and effective, improve customer relationships and enhance revenue growth. Instead of focusing on multi-year, resource- and time-intensive platform designs or migrations, we look deeper at your entire value chain to integrate strategies with impact. We use our specialization in analytics, digital interventions, and operations management—alongside deep industry expertise — to deliver solutions that help you outperform the competition. At EXL, it’s all about outcomes—your outcomes—and delivering success on your terms. Share your goals with us and together, we’ll optimize how you leverage data to drive your business forward. For more information, visit www.exlservice.com.
