Lead Data Scientist
High Tech Genesis
| Company | High Tech Genesis |
| Category | Data & Analytics |
| Location | Toronto |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Lead |
| Salary | Not stated by the employer |
| Posted | — |
| Last verified | 31 Jul 2026 |
| Source | Employer career page (recruitee) |
Description
Overview We are seeking an experienced Lead Data Scientist to design, develop, and deploy advanced AI and machine learning solutions that solve complex business challenges. This role requires hands-on expertise across the full data science lifecycle, from data exploration and model development to deployment and monitoring, while leading projects and collaborating with cross-functional teams. Key Responsibilities Design, build, and deploy AI, Machine Learning, Deep Learning, and Generative AI solutions. Translate business challenges into scalable data science solutions. Perform data extraction, preparation, analysis, feature engineering, model training, and evaluation. Develop proof-of-concepts, prototypes, and production-ready models. Deploy, monitor, maintain, and optimize machine learning solutions. Present technical findings and recommendations to technical and business stakeholders. Lead end-to-end data science initiatives and mentor team members. Collaborate with cross-functional engineering and product teams. Contribute to innovation through research, experimentation, and knowledge sharing. 7–10+ years of experience building and deploying machine learning and AI solutions (5+ years may be considered with a relevant Ph.D.). Strong expertise in Machine Learning, Deep Learning, Generative AI, LLMs, RAG, Vector Databases, and Agentic AI frameworks. Advanced programming experience with Python, PySpark, and SQL. Experience with ML/DL frameworks and cloud platforms such as AWS or Azure. Hands-on experience with Databricks and Hadoop. Strong understanding of data governance, privacy, and responsible AI practices. Excellent analytical, problem-solving, and communication skills. Master's degree in Computer Science, Data Science, Mathematics, Statistics, or a related quantitative field (Ph.D. is an asset).
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