Senior Data Scientist

2 weeks ago


Markham, Canada Xplore Inc. Full time

As a Senior Data Scientist at Xplore, you will drive measurable business outcomes by leading advanced modeling initiatives that directly support revenue growth, customer retention, and operational efficiency. Your work will enable smarter decision-making across the organization, powering strategies for churn reduction, upsell targeting, and network optimization. Beyond technical leadership, you’ll help shape the data science roadmap to align with high-priority business goals, mentor emerging talent, and deliver insights that translate into real commercial impact.Key responsibilities include:Lead complex modeling projects across technical and commercial domains, like: Churn propensity modeling and retention strategy designUpsell and cross-sell opportunity scoringProduct coverage estimation and e-coverage optimizationNetwork infrastructure investment optimization & anomaly detectionDefine modeling strategies and select appropriate algorithms (e.g., deep learning, time-series, probabilistic models, causal inference modeling).Evaluate trade-offs: accuracy vs latency vs interpretability; cost vs benefit; model maintenance and scalability.Collaborate with cross-functional teams: sales, marketing, product, operations, care, and network, to translate business needs into data science solutions driving measurable value.Own and oversee model deployment, monitoring, drift detection, and retraining pipelines.Ensure governance around data ethics, fairness, and privacy. Especially with customer data, usage logs, and location data.Mentor junior/intermediate data scientists; conduct code reviews and promote best practices (reproducibility, testing, documentation).Provide actionable insights to support executive decision-making and quantify business impact (e.g., revenue uplift, churn reduction, campaign ROI).The ideal candidate will possess:5–7+ years of experience in applied data science / machine learning, ideally with exposure to sales and marketing domains.Strong foundation in statistical modeling, causal inference, time-series forecasting, and uplift modeling to support customer insights and campaign effectiveness.Experience with A/B testing and experimentation frameworks to evaluate campaign effectiveness and optimize customer engagement strategies.Experience with large-scale modeling and distributed computing in cloud environments.Proficiency in Python, advanced ML frameworks, and MLops practices.Experience with customer data protection, privacy regulations, and ethical AI principles.Familiarity with marketing platforms or CRM systems (e.g., Salesforce) to support targeted outreach, segmentation, and lifecycle analytics.Proven track record of delivering measurable business impact (e.g., improved retention, increased ARPU, optimized campaign performance).Excellent communication skills, including with non-technical stakeholders; strong leadership and mentoring capabilities.Master’s or PhD preferred, but not required with strong experience.



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