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Builds GenAI and ML systems for actuarial finance, translating business problems into production-ready predictive/analytical solutions with explainability, governance, and operational controls.
The Data Scientist will collaborate with cross-functional teams to implement data-driven solutions, analyze complex data models, develop and deploy machine learning models for predictive analytics, and create data visualizations using tools like Azure Databricks, Apache Spark, and Power BI.
Own the full ML model lifecycle for credit and fraud risk decisions at a lease-to-own fintech, using Python, SQL, and structured-data ML algorithms to power credit approvals, line optimization, and loss forecasting.
Design and implement enterprise data platforms spanning ingestion, storage, transformation, and serving, with hands-on data engineering, governance (PDPA), and pipeline development to support analytics and AI/ML workloads.
Hybrid Machine Learning / Data Engineer About the Role An opportunity is available for a Hybrid Machine Learning / Data Engineer to join a team developing data-driven and machine learning solutions. Working across both…
Hybrid Machine Learning / Data Engineer About the Role An exciting opportunity is available for a Hybrid Machine Learning / Data Engineer to join a team developing production machine learning solutions using complex…
Data Scientist at Avride designs and evaluates metrics for autonomous vehicle safety and performance using Python, SQL, and statistical methods, analyzing real-world and simulated driving data.
This role involves developing machine learning models, designing data pipelines, and deploying models into production using Python, Spark, SQL, and FastAPI. The position is 100% remote and focuses on the end-to-end lifecycle of ML models within a dynamic consulting environment.
Analyzes battery and EV data to build reports and ML-ready datasets, using Python, SQL, and visualization tools in a manufacturing-focused energy tech company.
Build and deploy machine learning models and data pipelines for global clients, focusing on data engineering, model training, and MLOps with Python, PyTorch, and cloud platforms.
Designs, trains, and deploys AI/ML models and data pipelines to power predictive analytics for systematic trading in finance, using Python, SQL, and modern AI tools.
Senior Data Engineer at BC Transit designing and maintaining automated data pipelines, cloud data platform architectures, and scalable data products that power reporting, analytics, and ML across the organization.
Build and own production AI agents—the harnesses, tool layers, retrieval/RAG systems, eval/monitoring, and guardrails—for Tessera Labs' multi-agent enterprise transformation platform. Core tech: Python, TypeScript, LLM agent frameworks, RAG, traditional ML.
Directs the data engineering team at a major game studio, building scalable telemetry and AI-integrated platforms to turn player interactions into actionable insights while optimizing cloud costs.
Developing and deploying production ML/DL models for time series forecasting and financial market prediction in a DeFi and algorithmic trading product team, using Python, PyTorch, and gradient boosting frameworks.
Staff ML Engineer designing, building, and scaling production ML/AI systems—including LLMs, embeddings, recommendation systems, and forecasting—on a modern data platform using Python, SQL, and tools like Snowflake or Databricks for a SaaS client-experience platform serving appointment-based self-care businesses.
Designs, builds, and deploys enterprise-scale AI solutions including GenAI agents, RAG pipelines, and LLM-driven workflows using Azure AI services, while ensuring scalability, security, and Responsible AI compliance.
A Clinical Data Scientist using SQL, Python/Go, and BI tools like PowerBI and Tableau to analyze healthcare/pharmacy data, build dashboards, and measure program effectiveness in a hybrid role.
The Senior Data Engineer will design, build, and maintain scalable enterprise data pipelines and cloud-based data platforms using PySpark, Python, SQL, and Azure Data Factory. This role involves integrating complex business systems and partnering with data scientists to operationalize machine learning models and AI initiatives.
The Data Engineer will design and build production-grade AI and data solutions on Google Cloud to optimize stock, demand forecasting, and supply chain operations. The role involves managing data pipelines, feature engineering, and model deployment using Python, Vertex AI, and BigQuery.
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