Senior Data Scientist

🕒 September 15

🇨🇦 Canada – Remote

⏰ Full Time

🟠 Senior

📊 Data Scientist

👻 Ghost score 16%

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EXL

WebsiteLinkedInAll Job Openings

10,000+ employees

🏥 Healthcare

🛡️ Insurance

📦 Logistics

💰 $2M Venture Round on 2015-01

Healthcare • Insurance • Logistics

EXL is a business consulting and services firm that focuses on leveraging data to enhance business operations and decision-making. With a strong emphasis on collaboration and adaptability, EXL partners with organizations to address their unique needs and culture while integrating data science and technology solutions. The company's areas of expertise include operations management, decision analytics, digital transformation, and various industries such as healthcare, finance, and insurance. EXL's mission is to help clients drive business evolution and maintain competitive advantage through tailored solutions and effective use of data.

📋 Description

• Design, develop, and review machine learning solutions across insurance domains, including claims, underwriting, sales, and marketing • Own feature engineering using large-scale insurance datasets • Lead model selection, training, validation, and performance tuning • Handle highly imbalanced datasets, weak labels, and proxy targets • Translate business rules into ML features and hybrid rule-ML systems • Ensure model explainability, stability, and governance aligned with insurance and regulatory expectations • Act as the client-facing data scientist and manage client relationships • Prepare demos and sprint review materials • Translate high-level business problems into defined analytics use cases, modeling approaches, and delivery plans • Participate in architecture and solution design discussions, model walkthroughs, UAT discussions, and model acceptance criteria definition • Communicate risks, dependencies, and delivery trade-offs • Coordinate with offshore teams to ensure delivery quality • Work with data engineering and platform teams to shape analytical data models and feature stores • Ensure production readiness of models • Contribute to MLOps design, including model versioning, monitoring, and retraining strategies • Contribute to deployment patterns on modern analytics platforms and ensure enterprise standards for scalability, reliability, and auditability

🎯 Requirements

• 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 • Strong hands-on experience with Python, including pandas, scikit-learn, XGBoost / LightGBM • Statistical modeling and ML algorithms, including classification, regression, and segmentation • Deep understanding of feature engineering on transactional / behavioral data • Deep understanding of imbalanced classification techniques • Deep understanding of model evaluation, stability, and drift monitoring • Experience working with SQL and large-scale datasets • 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 • Comfortable working across time zones and in a matrix delivery model • Familiarity with modern ML platforms, cloud data environments, or analytics fabrics is a plus • Exposure to model governance and regulatory expectations, Explainable AI (XAI) techniques, and MLOps pipelines and CI/CD for analytics is preferred / nice-to-have

🏖️ Benefits

• Work From Home / remote work

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