Founded in 2017, Lovelytics has helped some of the most complex enterprises across industries such as Energy & Utilities, Media & Entertainment, Manufacturing and Retail & CPG, modernize their data and put AI to work, not in a deck, but in production.

Our work spans the full data and AI lifecycle: Data Strategy &

• Advisory, Data Engineering, Analytics &

• Visualization, Generative AI &

• ML, and Cloud Migration &

• Modernization - all delivered on Databricks, with deep partnerships across AWS, Azure, and GCP. In the last year, Lovelytics has grown from 85 to 500+ people across the Americas, all while keeping the technically excellent, low-ego culture that makes the work worth doing, earning us a Best Places to Work recognition and a spot among Databricks' top partners. Lovelytics is seeking a Data Scientist Architect with hands-on experience delivering client-facing, enterprise-grade machine learning and advanced analytics solutions, particularly on the Databricks platform. As part of our growing Data Science practice, this role offers an exciting prospect to lead technical strategy, design end-to-end ML pipelines, and drive pre-sales engagements from initial scoping to final delivery. Our ideal candidate blends deep technical expertise across predictive modeling and modern AI frameworks with seasoned consulting acumen to influence both technical execution teams and C-suite executives. ROI, revenue impact, cost reduction) alongside technical performance targets for every engagement. Lead technical scoping, feasibility assessments and solution design for proposals, Statements of Work and client pitches. Design scalable, secure and maintainable end-to-end multi-layer ML/AI pipelines, spanning data analysis, feature engineering, model training, deployment and MLOps. Direct cross-functional delivery teams of Data Scientists,



Data Engineers and ML Engineers to execute solutions aligned with architectural standards. Establish code quality standards, model validation protocols and technical best practices to prevent technical debt and ensure system reliability. Articulate technical concepts, model trade-offs and operational risks clearly to both technical teams and non-technical C-suite stakeholders. Conduct client enablement workshops and knowledge transfer sessions to build internal capability and ensure long-term solution sustainability. Bachelor’s or Master’s degree in Computer Science, Engineering, Statistics, economics or a related field. ~7+ years of experience in data science &

• AI/ML, including large-scale solution deployments. ~Strong communication skills with the ability to influence technical and executive stakeholders. ~ Proven track record designing and implementing modern data science solutions in at least two of the following areas: forecasting, anomaly detection, recommendation system, computer vision, risk modeling or mathematical optimization. ~ Expert knowledge of Python, SQL and strong hands-on experience with Databricks (Unity Catalog, MLFlow, Delta Tables, etc.). ~ Proficiency with commercial and open-source LLM APIs and tooling like Hugging Face, LangChain, DSPY etc, as well as coding assistants. ~ Experience with rapid prototyping and creating proofs of concept, technical presales presentations and pricing for engagements. ~ Meaningful, cutting-edge projects in Data Science &

• AI/ML domain with clients across industries, from Fortune 500 firms to disruptive startups. Rapid learning and mentorship opportunities with Data &

• AI thought leaders and practitioners. A culture of experimentation, innovation and continuous improvement. We consider all applicants without regard to race, color, religion, age, ancestry, ethnicity, gender, gender identity, gender expression, sexual orientation, veteran status, or disability. #

📌 Architect, Data Science (Toronto)
🏢 Lovelytics
📍 Toronto