EXL (NASDAQ: EXLS) is a global analytics and digital solutions company that partners with clients to improve business outcomes and unlock growth. Bringing together deep domain expertise with robust data, powerful analytics, cloud, and AI, we create agile, scalable solutions and execute complex operations for the world’s leading corporations in industries including insurance, healthcare, banking and financial services, media, and retail, among others. Focused on creating value from data for driving faster decision‑making and transforming operating models, EXL was founded on the core values of innovation, collaboration, excellence, integrity and respect. Headquartered in New York, our team is over 40,000 strong, with more than 50 offices spanning six continents. For information, visit

For the past 20 years, EXL has worked as a strategic partner and won awards in its approach to helping its clients solve business challenges such as digital transformation, improving customer experience, streamlining business operations, taking products to market faster, improving corporate finance, building models to become compliant more quickly with new regulations, turning volumes of data into business opportunities, creating new channels for growth and better adapting to change. The business operates within four business units: Insurance, Health, Analytics, and Emerging businesses.

Job Description

We are seeking a senior data scientist to lead delivery of advanced analytics and machine learning solutions for a large scale transformation program within insurance practice. This role is critical to bridging business objectives, data science execution, and delivery excellence. The individual will remain deeply involved in model development and technical design, while also coordinate with offshore team to ensure delivery quality.





Responsibilities

- Technical & Solution Leadership: Design, develop, and review machine learning solutions across insurance domains, including claims, underwriting, sales and marketing.
- Take ownership of model selection, training, validation, performance tuning, handling highly imbalanced datasets, weak labels, and proxy targets.
- Translate business rules into ML features / hybrid rule‑ML systems, ensuring model explainability, stability, and governance aligned with insurance and regulatory expectations (e.g., interpretable ML, bias mitigation).
- Act as the client facing data scientist who manages client relationships, prepares demos and sprint review materials.
- Translate high‑level business problems into well‑defined analytics use cases, modeling approaches and delivery plans, architecture and solution design discussions, model walkthroughs with technical and business stakeholders, UAT discussions and model acceptance criteria definition.
- Communicate risks, dependencies, and delivery trade‑offs early and clearly.
- Work with data engineering and platform teams to shape analytical data models and feature stores, ensure production readiness of models, contribute to deployment patterns on contemporary analytics platforms, and ensure models meet enterprise standards for scalability, reliability, and auditability.

Experience & Domain





- 5 – 8 years of experience in advanced analytics / data science.
- Insurance domain experience (P&C;, Life, Health, Group Benefits, or Claims) strongly preferred.
- Proven experience delivering end‑to‑end ML solutions in production environments.

Technical Skills

- Strong hands‑on experience in statistical modeling and ML algorithms (classification, regression, segmentation).
- Deep understanding of feature engineering on transactional / behavioral data, imbalanced classification techniques, model evaluation, stability, and drift monitoring, working with SQL and large‑scale datasets.
- Familiarity with modern ML platforms, cloud data environments, or analytics fabrics is a plus.

Stakeholder Management & Communication

- Experience working with offshore or distributed data science teams.
- Strong storytelling skills to explain complex analytical concepts to non‑technical stakeholders, onsite leadership and clients, and comfortable working across time zones and in a matrix delivery model.

Preferred / Nice‑to-Have

- Exposure to model governance and regulatory expectations.
- MLOps pipelines and CI/CD for analytics.

What We Offer

- EXL Analytics offers an exciting, fast paced and innovative environment with a group of sharp and entrepreneurial professionals who are eager to influence business decisions.
- Opportunity to learn many aspects of businesses that clients engage in, effective teamwork and time‑management skills for personal and professional growth.
- Investment in training on all aspects of analytics and leading analytical tools and techniques.
- Guidance and coaching through a mentoring program.
- Experience setting the stage for further growth and development within the company and beyond.

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📌 Senior Data Scientist (Toronto)
🏢 exl
📍 Toronto